{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# `vaex` @ PyData London 2019\n",
    "## New York Taxi Dataset (2009-2015): Exploratory Data Analysis and Machine Learning example\n",
    "\n",
    "https://www1.nyc.gov/site/tlc/about/tlc-trip-record-data.page"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T13:56:53.343940Z",
     "start_time": "2019-07-13T13:56:53.341081Z"
    }
   },
   "outputs": [],
   "source": [
    "import vaex\n",
    "from vaex.ui.colormaps import cm_plusmin\n",
    "import warnings; warnings.simplefilter('ignore')\n",
    "\n",
    "\n",
    "import pylab as plt\n",
    "import numpy as np\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:06:05.558587Z",
     "start_time": "2019-07-13T14:06:05.440488Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total 1.5T\r\n",
      "drwxr-xr-x 2 maartenbreddels maartenbreddels 4.0K Jul  5 10:04 airlines-us\r\n",
      "-rw-r--r-- 1 maartenbreddels maartenbreddels 1.2T Jun 30 16:30 gaia-dr2-sort-by-source_id.hdf5\r\n",
      "drwxr-xr-x 2 maartenbreddels maartenbreddels 4.0K Jul  6 19:11 GDELT\r\n",
      "drwx------ 2 root            root             16K Jun 28 19:58 lost+found\r\n",
      "drwxr-xr-x 2 maartenbreddels maartenbreddels 4.0K Jul  8 19:33 misc\r\n",
      "-rwxrwxrwx 1 maartenbreddels maartenbreddels 108G May  2 14:16 yellow_taxi_2009_2015_f32.hdf5\r\n",
      "-rwxrwxrwx 1 maartenbreddels maartenbreddels 164G Apr 12 21:31 yellow_taxi_2009_2015.hdf5\r\n",
      "-rw-r--r-- 1 maartenbreddels maartenbreddels  12G Jul  7 01:03 yellow_taxi_2015_f32.hdf5\r\n"
     ]
    }
   ],
   "source": [
    "!ls -lh /data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:06:46.841761Z",
     "start_time": "2019-07-13T14:06:46.795265Z"
    }
   },
   "outputs": [],
   "source": [
    "df_gaia = vaex.open('/data/gaia-dr2-sort-by-source_id.hdf5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:06:47.215899Z",
     "start_time": "2019-07-13T14:06:47.113039Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th>#                                        </th><th>solution_id        </th><th>designation                    </th><th>source_id          </th><th>random_index  </th><th>ref_epoch  </th><th>ra                </th><th>ra_error            </th><th>dec                  </th><th>dec_error          </th><th>parallax           </th><th>parallax_error     </th><th>parallax_over_error  </th><th>pmra              </th><th>pmra_error         </th><th>pmdec              </th><th>pmdec_error        </th><th>ra_dec_corr        </th><th>ra_parallax_corr  </th><th>ra_pmra_corr  </th><th>ra_pmdec_corr  </th><th>dec_parallax_corr   </th><th>dec_pmra_corr       </th><th>dec_pmdec_corr     </th><th>parallax_pmra_corr  </th><th>parallax_pmdec_corr  </th><th>pmra_pmdec_corr     </th><th>astrometric_n_obs_al  </th><th>astrometric_n_obs_ac  </th><th>astrometric_n_good_obs_al  </th><th>astrometric_n_bad_obs_al  </th><th>astrometric_gof_al  </th><th>astrometric_chi2_al  </th><th>astrometric_excess_noise  </th><th>astrometric_excess_noise_sig  </th><th>astrometric_params_solved  </th><th>astrometric_primary_flag  </th><th>astrometric_weight_al  </th><th>astrometric_pseudo_colour  </th><th>astrometric_pseudo_colour_error  </th><th>mean_varpi_factor_al  </th><th>astrometric_matched_observations  </th><th>visibility_periods_used  </th><th>astrometric_sigma5d_max  </th><th>frame_rotator_object_type  </th><th>matched_observations  </th><th>duplicated_source  </th><th>phot_g_n_obs  </th><th>phot_g_mean_flux  </th><th>phot_g_mean_flux_error  </th><th>phot_g_mean_flux_over_error  </th><th>phot_g_mean_mag  </th><th>phot_bp_n_obs  </th><th>phot_bp_mean_flux  </th><th>phot_bp_mean_flux_error  </th><th>phot_bp_mean_flux_over_error  </th><th>phot_bp_mean_mag  </th><th>phot_rp_n_obs  </th><th>phot_rp_mean_flux  </th><th>phot_rp_mean_flux_error  </th><th>phot_rp_mean_flux_over_error  </th><th>phot_rp_mean_mag  </th><th>phot_bp_rp_excess_factor  </th><th>phot_proc_mode  </th><th>bp_rp    </th><th>bp_g              </th><th>g_rp              </th><th>radial_velocity  </th><th>radial_velocity_error  </th><th>rv_nb_transits  </th><th>rv_template_teff  </th><th>rv_template_logg  </th><th>rv_template_fe_h  </th><th>phot_variable_flag  </th><th>l                 </th><th>b                  </th><th>ecl_lon           </th><th>ecl_lat            </th><th>priam_flags  </th><th>teff_val  </th><th>teff_percentile_lower  </th><th>teff_percentile_upper  </th><th>a_g_val  </th><th>a_g_percentile_lower  </th><th>a_g_percentile_upper  </th><th>e_bp_min_rp_val  </th><th>e_bp_min_rp_percentile_lower  </th><th>e_bp_min_rp_percentile_upper  </th><th>flame_flags  </th><th>radius_val  </th><th>radius_percentile_lower  </th><th>radius_percentile_upper  </th><th>lum_val   </th><th>lum_percentile_lower  </th><th>lum_percentile_upper  </th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td><i style='opacity: 0.6'>0</i>            </td><td>1635721458409799680</td><td>b'Gaia DR2 4295806720'         </td><td>4295806720         </td><td>833719442     </td><td>2015.5     </td><td>44.9961536841596  </td><td>0.119381727827906   </td><td>0.005615806210679649 </td><td>0.12287249077395065</td><td>0.07144782399869501</td><td>0.16248493485095816</td><td>0.43971968           </td><td>11.733411429340324</td><td>0.2431241681877592 </td><td>-4.7759340851709   </td><td>0.2389884371856387 </td><td>0.022670548        </td><td>0.27376112        </td><td>-0.061221834  </td><td>0.09342154     </td><td>-0.43380169999999996</td><td>-0.10258209         </td><td>-0.23457742        </td><td>0.2862106           </td><td>0.24838115           </td><td>0.30606467          </td><td>107                   </td><td>0                     </td><td>106                        </td><td>1                         </td><td>1.6358627000000001  </td><td>125.30832            </td><td>0.0                       </td><td>0.0                           </td><td>31                         </td><td>False                     </td><td>1.6281219999999998     </td><td>1.6129292688600716         </td><td>0.03975095740667449              </td><td>0.026966427           </td><td>13                                </td><td>10                       </td><td>0.25016737               </td><td>0                          </td><td>13                    </td><td>False              </td><td>103           </td><td>1635.9507708728468</td><td>2.7757613305963007      </td><td>589.3701                     </td><td>17.65394         </td><td>10             </td><td>785.6408778060331  </td><td>8.304744041442405        </td><td>94.601456                     </td><td>18.113329         </td><td>11             </td><td>1205.3932347369573 </td><td>12.695619867587247       </td><td>94.9456                       </td><td>17.059097         </td><td>1.2170502                 </td><td>0               </td><td>1.0542316</td><td>0.45938873        </td><td>0.5948429000000001</td><td>nan              </td><td>nan                    </td><td>0               </td><td>nan               </td><td>nan               </td><td>nan               </td><td>b'NOT_AVAILABLE'    </td><td>176.9510737567222 </td><td>-48.901521688994805</td><td>42.5337243367526  </td><td>-16.32957311107743 </td><td>nan          </td><td>nan       </td><td>nan                    </td><td>nan                    </td><td>nan      </td><td>nan                   </td><td>nan                   </td><td>nan              </td><td>nan                           </td><td>nan                           </td><td>nan          </td><td>nan         </td><td>nan                      </td><td>nan                      </td><td>nan       </td><td>nan                   </td><td>nan                   </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1</i>            </td><td>1635721458409799680</td><td>b'Gaia DR2 34361129088'        </td><td>34361129088        </td><td>1253687186    </td><td>2015.5     </td><td>45.00431616420765 </td><td>0.13221516031053107 </td><td>0.021045032689712983 </td><td>0.15033009946029466</td><td>3.48677407917816   </td><td>0.1943677537725032 </td><td>17.939056            </td><td>30.2997273525487  </td><td>0.2890571540060363 </td><td>20.102047674607906 </td><td>0.2904121164006919 </td><td>0.06490505         </td><td>0.10328879        </td><td>-3.8125843e-05</td><td>0.010977124    </td><td>-0.5181503          </td><td>-0.15682727         </td><td>-0.25213727        </td><td>0.25715247          </td><td>0.36133286           </td><td>0.21847394          </td><td>97                    </td><td>0                     </td><td>97                         </td><td>0                         </td><td>3.1044097           </td><td>139.97816            </td><td>0.4393295485806768        </td><td>2.2560181660871423            </td><td>31                         </td><td>False                     </td><td>1.285051               </td><td>1.3322381786391089         </td><td>0.043729691466259976             </td><td>0.030602371           </td><td>11                                </td><td>9                        </td><td>0.29393765               </td><td>0                          </td><td>11                    </td><td>False              </td><td>96            </td><td>1712.9128925457007</td><td>3.0338739347619077      </td><td>564.59595                    </td><td>17.604027        </td><td>11             </td><td>397.3368347119427  </td><td>13.369227259151073       </td><td>29.720254999999998            </td><td>18.85349          </td><td>10             </td><td>2155.4795941459947 </td><td>8.25350128363993         </td><td>261.15942                     </td><td>16.428060000000002</td><td>1.4903364                 </td><td>0               </td><td>2.4254303</td><td>1.249464          </td><td>1.1759663         </td><td>nan              </td><td>nan                    </td><td>0               </td><td>nan               </td><td>nan               </td><td>nan               </td><td>b'NOT_AVAILABLE'    </td><td>176.94278716312405</td><td>-48.88493841774036 </td><td>42.54656815575859 </td><td>-16.317213719979975</td><td>nan          </td><td>nan       </td><td>nan                    </td><td>nan                    </td><td>nan      </td><td>nan                   </td><td>nan                   </td><td>nan              </td><td>nan                           </td><td>nan                           </td><td>nan          </td><td>nan         </td><td>nan                      </td><td>nan                      </td><td>nan       </td><td>nan                   </td><td>nan                   </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>2</i>            </td><td>1635721458409799680</td><td>b'Gaia DR2 38655544960'        </td><td>38655544960        </td><td>1168973894    </td><td>2015.5     </td><td>45.004974244984105</td><td>0.029723176168001464</td><td>0.019877000365797717 </td><td>0.0398615194906984 </td><td>3.1212565825574363 </td><td>0.04667520041451068</td><td>66.87184             </td><td>29.669773387717747</td><td>0.07106567711614904</td><td>19.225962799772443 </td><td>0.08279741152631212</td><td>0.11690165         </td><td>0.2090516         </td><td>-0.14794418   </td><td>-0.082815714   </td><td>-0.6151166          </td><td>-0.4523399          </td><td>-0.59776425        </td><td>0.45273238          </td><td>0.47702566           </td><td>0.595477            </td><td>104                   </td><td>0                     </td><td>104                        </td><td>0                         </td><td>-2.2898765          </td><td>69.61933             </td><td>0.0                       </td><td>0.0                           </td><td>31                         </td><td>False                     </td><td>54.20531999999999      </td><td>1.5148504032402288         </td><td>0.010003998099121137             </td><td>0.07058261            </td><td>12                                </td><td>9                        </td><td>0.10163828               </td><td>0                          </td><td>12                    </td><td>False              </td><td>103           </td><td>41605.42089500058 </td><td>18.392505474272053      </td><td>2262.0854                    </td><td>14.140491        </td><td>11             </td><td>17692.585419434203 </td><td>53.957682875030116       </td><td>327.89743                     </td><td>14.731910000000001</td><td>11             </td><td>34351.87449020634  </td><td>58.427462958732775       </td><td>587.94055                     </td><td>13.422044         </td><td>1.2509058000000002        </td><td>0               </td><td>1.309866 </td><td>0.5914191999999999</td><td>0.71844673        </td><td>nan              </td><td>nan                    </td><td>0               </td><td>nan               </td><td>nan               </td><td>nan               </td><td>b'NOT_AVAILABLE'    </td><td>176.94476069003898</td><td>-48.88527495232597 </td><td>42.54686709098933 </td><td>-16.318523323705843</td><td>100001.0     </td><td>4962.0    </td><td>4770.505               </td><td>5050.6665              </td><td>0.032    </td><td>0.0149                </td><td>0.2091                </td><td>0.016            </td><td>0.0069                        </td><td>0.0728                        </td><td>200111.0     </td><td>0.5863995   </td><td>0.5659911999999999       </td><td>0.63442224               </td><td>0.18780576</td><td>0.18156888            </td><td>0.19404264            </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>3</i>            </td><td>1635721458409799680</td><td>b'Gaia DR2 309238066432'       </td><td>309238066432       </td><td>716364491     </td><td>2015.5     </td><td>44.99503703932583 </td><td>0.3748451704441453  </td><td>0.03815183599451371  </td><td>0.354580932399439  </td><td>1.5788410668677395 </td><td>0.4509078829430168 </td><td>3.5014714999999996   </td><td>0.9185563546406772</td><td>0.8071335238976993 </td><td>-0.4685586426340295</td><td>0.7201817396537079 </td><td>0.042778816        </td><td>0.14737031        </td><td>-0.08400111   </td><td>0.071659945    </td><td>-0.175486           </td><td>0.009628623000000001</td><td>-0.06346788        </td><td>0.19779278          </td><td>0.17691185           </td><td>0.061723847000000005</td><td>114                   </td><td>0                     </td><td>114                        </td><td>0                         </td><td>-0.38584504         </td><td>102.75944            </td><td>0.0                       </td><td>0.0                           </td><td>31                         </td><td>False                     </td><td>0.1383114              </td><td>1.2159144402017843         </td><td>0.1151187960793006               </td><td>-0.07122756           </td><td>13                                </td><td>10                       </td><td>0.71777946               </td><td>0                          </td><td>13                    </td><td>False              </td><td>114           </td><td>263.32165329152957</td><td>1.644274128985754       </td><td>160.14462                    </td><td>19.63715         </td><td>9              </td><td>50.62248230415713  </td><td>4.981187273921231        </td><td>10.162734                     </td><td>21.090529999999998</td><td>9              </td><td>355.4098452181598  </td><td>7.532196715416053        </td><td>47.185417                     </td><td>18.385096         </td><td>1.5419633                 </td><td>0               </td><td>2.7054348</td><td>1.4533806         </td><td>1.2520542         </td><td>nan              </td><td>nan                    </td><td>0               </td><td>nan               </td><td>nan               </td><td>nan               </td><td>b'NOT_AVAILABLE'    </td><td>176.91426520135354</td><td>-48.87974729251865 </td><td>42.54254808202412 </td><td>-16.29813865533474 </td><td>nan          </td><td>nan       </td><td>nan                    </td><td>nan                    </td><td>nan      </td><td>nan                   </td><td>nan                   </td><td>nan              </td><td>nan                           </td><td>nan                           </td><td>nan          </td><td>nan         </td><td>nan                      </td><td>nan                      </td><td>nan       </td><td>nan                   </td><td>nan                   </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>4</i>            </td><td>1635721458409799680</td><td>b'Gaia DR2 343597448960'       </td><td>343597448960       </td><td>1007197339    </td><td>2015.5     </td><td>44.963895325304286</td><td>0.1672591368280593  </td><td>0.04359518482272568  </td><td>0.15843084907464913</td><td>0.1124232337595906 </td><td>0.19677095501039435</td><td>0.5713406            </td><td>6.778646355438693 </td><td>0.34015943821418143</td><td>-1.5922073291150058</td><td>0.3142620551370774 </td><td>0.095711425        </td><td>0.25192115        </td><td>-0.09463473   </td><td>0.11687218     </td><td>-0.14148766         </td><td>0.10662418          </td><td>0.001552241        </td><td>0.1539189           </td><td>0.0099432925         </td><td>0.1900829           </td><td>114                   </td><td>0                     </td><td>111                        </td><td>3                         </td><td>0.7612909000000001  </td><td>116.762924           </td><td>0.4379146032596523        </td><td>1.164799959704128             </td><td>31                         </td><td>False                     </td><td>0.7568838999999999     </td><td>1.5231059896314436         </td><td>0.0485359898688584               </td><td>0.009498954           </td><td>13                                </td><td>9                        </td><td>0.31823537               </td><td>0                          </td><td>13                    </td><td>False              </td><td>109           </td><td>1037.4128672255997</td><td>2.2948097285863445      </td><td>452.06924000000004           </td><td>18.148487        </td><td>9              </td><td>446.11647691960206 </td><td>12.472760208872558       </td><td>35.76726                      </td><td>18.727767999999998</td><td>10             </td><td>851.5124585934102  </td><td>10.580999260922557       </td><td>80.47561999999999             </td><td>17.436443         </td><td>1.2508317                 </td><td>0               </td><td>1.2913246</td><td>0.57928085        </td><td>0.71204376        </td><td>nan              </td><td>nan                    </td><td>0               </td><td>nan               </td><td>nan               </td><td>nan               </td><td>b'NOT_AVAILABLE'    </td><td>176.8754231026413 </td><td>-48.89837989670807 </td><td>42.513191444633726</td><td>-16.28380551789907 </td><td>nan          </td><td>nan       </td><td>nan                    </td><td>nan                    </td><td>nan      </td><td>nan                   </td><td>nan                   </td><td>nan              </td><td>nan                           </td><td>nan                           </td><td>nan          </td><td>nan         </td><td>nan                      </td><td>nan                      </td><td>nan       </td><td>nan                   </td><td>nan                   </td></tr>\n",
       "<tr><td>...                                      </td><td>...                </td><td>...                            </td><td>...                </td><td>...           </td><td>...        </td><td>...               </td><td>...                 </td><td>...                  </td><td>...                </td><td>...                </td><td>...                </td><td>...                  </td><td>...               </td><td>...                </td><td>...                </td><td>...                </td><td>...                </td><td>...               </td><td>...           </td><td>...            </td><td>...                 </td><td>...                 </td><td>...                </td><td>...                 </td><td>...                  </td><td>...                 </td><td>...                   </td><td>...                   </td><td>...                        </td><td>...                       </td><td>...                 </td><td>...                  </td><td>...                       </td><td>...                           </td><td>...                        </td><td>...                       </td><td>...                    </td><td>...                        </td><td>...                              </td><td>...                   </td><td>...                               </td><td>...                      </td><td>...                      </td><td>...                        </td><td>...                   </td><td>...                </td><td>...           </td><td>...               </td><td>...                     </td><td>...                          </td><td>...              </td><td>...            </td><td>...                </td><td>...                      </td><td>...                           </td><td>...               </td><td>...            </td><td>...                </td><td>...                      </td><td>...                           </td><td>...               </td><td>...                       </td><td>...             </td><td>...      </td><td>...               </td><td>...               </td><td>...              </td><td>...                    </td><td>...             </td><td>...               </td><td>...               </td><td>...               </td><td>...                 </td><td>...               </td><td>...                </td><td>...               </td><td>...                </td><td>...          </td><td>...       </td><td>...                    </td><td>...                    </td><td>...      </td><td>...                   </td><td>...                   </td><td>...              </td><td>...                           </td><td>...                           </td><td>...          </td><td>...         </td><td>...                      </td><td>...                      </td><td>...       </td><td>...                   </td><td>...                   </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1,692,919,130</i></td><td>1635721458409799680</td><td>b'Gaia DR2 6917528963217645568'</td><td>6917528963217645568</td><td>711904833     </td><td>2015.5     </td><td>314.98351260118864</td><td>6.1917502919260725  </td><td>-0.017961413757040568</td><td>1.9976645630944625 </td><td>nan                </td><td>nan                </td><td>nan                  </td><td>nan               </td><td>nan                </td><td>nan                </td><td>nan                </td><td>-0.9468261999999998</td><td>nan               </td><td>nan           </td><td>nan            </td><td>nan                 </td><td>nan                 </td><td>nan                </td><td>nan                 </td><td>nan                  </td><td>nan                 </td><td>256                   </td><td>0                     </td><td>255                        </td><td>1                         </td><td>0.09006713          </td><td>251.34973            </td><td>0.0                       </td><td>0.0                           </td><td>3                          </td><td>False                     </td><td>0.035857863999999996   </td><td>nan                        </td><td>nan                              </td><td>-0.18235932           </td><td>30                                </td><td>6                        </td><td>13.550334                </td><td>0                          </td><td>36                    </td><td>False              </td><td>276           </td><td>130.46916462266304</td><td>0.8370730500448316      </td><td>155.86354                    </td><td>20.399595        </td><td>0              </td><td>nan                </td><td>nan                      </td><td>nan                           </td><td>nan               </td><td>0              </td><td>nan                </td><td>nan                      </td><td>nan                           </td><td>nan               </td><td>nan                       </td><td>2               </td><td>nan      </td><td>nan               </td><td>nan               </td><td>nan              </td><td>nan                    </td><td>0               </td><td>nan               </td><td>nan               </td><td>nan               </td><td>b'NOT_AVAILABLE'    </td><td>48.891138199898776</td><td>-28.255063825226554</td><td>317.44227847436525</td><td>16.323719462219874 </td><td>nan          </td><td>nan       </td><td>nan                    </td><td>nan                    </td><td>nan      </td><td>nan                   </td><td>nan                   </td><td>nan              </td><td>nan                           </td><td>nan                           </td><td>nan          </td><td>nan         </td><td>nan                      </td><td>nan                      </td><td>nan       </td><td>nan                   </td><td>nan                   </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1,692,919,131</i></td><td>1635721458409799680</td><td>b'Gaia DR2 6917528993281571840'</td><td>6917528993281571840</td><td>1057759634    </td><td>2015.5     </td><td>314.9904017564393 </td><td>0.2686243051566997  </td><td>-0.008367585301478679</td><td>0.13220884263955485</td><td>0.9767377244025096 </td><td>0.20966425878115624</td><td>4.658580000000001    </td><td>-8.789568499444613</td><td>0.6024182711252432 </td><td>-9.887007450999603 </td><td>0.3609798630506912 </td><td>-0.71226794        </td><td>-0.32785413       </td><td>-0.79407966   </td><td>0.67225677     </td><td>0.6483722           </td><td>0.66855806          </td><td>-0.88509864        </td><td>0.31642532          </td><td>-0.57081836          </td><td>-0.71771705         </td><td>288                   </td><td>0                     </td><td>286                        </td><td>2                         </td><td>0.15602541          </td><td>284.04306            </td><td>0.10468895650873274       </td><td>0.1926633779846534            </td><td>31                         </td><td>False                     </td><td>1.5025905000000002     </td><td>1.4398141313394808         </td><td>0.024217901524240717             </td><td>-0.18079054           </td><td>33                                </td><td>7                        </td><td>0.6392459                </td><td>0                          </td><td>35                    </td><td>False              </td><td>300           </td><td>1708.7844181229475</td><td>1.7183001457312599      </td><td>994.4621                     </td><td>17.606647        </td><td>0              </td><td>nan                </td><td>nan                      </td><td>nan                           </td><td>nan               </td><td>0              </td><td>nan                </td><td>nan                      </td><td>nan                           </td><td>nan               </td><td>nan                       </td><td>2               </td><td>nan      </td><td>nan               </td><td>nan               </td><td>nan              </td><td>nan                    </td><td>0               </td><td>nan               </td><td>nan               </td><td>nan               </td><td>b'NOT_AVAILABLE'    </td><td>48.90450543399686 </td><td>-28.25599336436905 </td><td>317.4520713869125 </td><td>16.330873481856276 </td><td>nan          </td><td>nan       </td><td>nan                    </td><td>nan                    </td><td>nan      </td><td>nan                   </td><td>nan                   </td><td>nan              </td><td>nan                           </td><td>nan                           </td><td>nan          </td><td>nan         </td><td>nan                      </td><td>nan                      </td><td>nan       </td><td>nan                   </td><td>nan                   </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1,692,919,132</i></td><td>1635721458409799680</td><td>b'Gaia DR2 6917528993281819008'</td><td>6917528993281819008</td><td>49260802      </td><td>2015.5     </td><td>315.00503877002456</td><td>0.9552057496355612  </td><td>-0.005736736411478651</td><td>0.4779456781063856 </td><td>-0.1827374708936312</td><td>0.6920683360998278 </td><td>-0.26404542          </td><td>-2.893619483581229</td><td>2.08879809691233   </td><td>-10.430692969558967</td><td>1.3486921231345796 </td><td>-0.6087746         </td><td>-0.27599064       </td><td>-0.81443137   </td><td>0.5377084      </td><td>0.5961895           </td><td>0.5714225           </td><td>-0.9083530000000001</td><td>0.24399203          </td><td>-0.50589395          </td><td>-0.5980193          </td><td>262                   </td><td>0                     </td><td>260                        </td><td>2                         </td><td>0.8898790000000001  </td><td>274.92728            </td><td>0.0                       </td><td>0.0                           </td><td>31                         </td><td>False                     </td><td>0.15255077             </td><td>1.4387809895123045         </td><td>0.08102495521913795              </td><td>-0.17755668           </td><td>30                                </td><td>7                        </td><td>2.18716                  </td><td>0                          </td><td>32                    </td><td>False              </td><td>276           </td><td>334.30089812181717</td><td>1.2490521307085771      </td><td>267.64367999999996           </td><td>19.378021        </td><td>0              </td><td>nan                </td><td>nan                      </td><td>nan                           </td><td>nan               </td><td>0              </td><td>nan                </td><td>nan                      </td><td>nan                           </td><td>nan               </td><td>nan                       </td><td>2               </td><td>nan      </td><td>nan               </td><td>nan               </td><td>nan              </td><td>nan                    </td><td>0               </td><td>nan               </td><td>nan               </td><td>nan               </td><td>b'NOT_AVAILABLE'    </td><td>48.915662985463   </td><td>-28.26715505980319 </td><td>317.46745740038915</td><td>16.329098939790963 </td><td>nan          </td><td>nan       </td><td>nan                    </td><td>nan                    </td><td>nan      </td><td>nan                   </td><td>nan                   </td><td>nan              </td><td>nan                           </td><td>nan                           </td><td>nan          </td><td>nan         </td><td>nan                      </td><td>nan                      </td><td>nan       </td><td>nan                   </td><td>nan                   </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1,692,919,133</i></td><td>1635721458409799680</td><td>b'Gaia DR2 6917528993283204480'</td><td>6917528993283204480</td><td>916652582     </td><td>2015.5     </td><td>314.9990508711522 </td><td>1.0200557955731553  </td><td>-0.002570580482067311</td><td>0.4785034535013264 </td><td>1.1944658684106606 </td><td>0.7390532046807501 </td><td>1.6162108999999998   </td><td>-4.969626151660421</td><td>2.3067588023833188 </td><td>-3.8381494703152055</td><td>1.3348034677367284 </td><td>-0.6952682         </td><td>-0.19890665       </td><td>-0.81487304   </td><td>0.6605273      </td><td>0.5953058000000001  </td><td>0.6642836999999999  </td><td>-0.8895016         </td><td>0.19809727          </td><td>-0.5282448000000001  </td><td>-0.72904134         </td><td>270                   </td><td>9                     </td><td>268                        </td><td>2                         </td><td>-0.077295646        </td><td>260.5681             </td><td>0.0                       </td><td>0.0                           </td><td>31                         </td><td>False                     </td><td>0.1274624              </td><td>1.4639756577435132         </td><td>0.09127171084755213              </td><td>-0.18912020000000002  </td><td>31                                </td><td>7                        </td><td>2.3505502000000003       </td><td>0                          </td><td>33                    </td><td>False              </td><td>283           </td><td>284.94374839895426</td><td>1.2279312655182504      </td><td>232.05186                    </td><td>19.551468        </td><td>0              </td><td>nan                </td><td>nan                      </td><td>nan                           </td><td>nan               </td><td>0              </td><td>nan                </td><td>nan                      </td><td>nan                           </td><td>nan               </td><td>nan                       </td><td>2               </td><td>nan      </td><td>nan               </td><td>nan               </td><td>nan              </td><td>nan                    </td><td>0               </td><td>nan               </td><td>nan               </td><td>nan               </td><td>b'NOT_AVAILABLE'    </td><td>48.91521924800499 </td><td>-28.26039290592401 </td><td>317.4624588295149 </td><td>16.333881134855314 </td><td>nan          </td><td>nan       </td><td>nan                    </td><td>nan                    </td><td>nan      </td><td>nan                   </td><td>nan                   </td><td>nan              </td><td>nan                           </td><td>nan                           </td><td>nan          </td><td>nan         </td><td>nan                      </td><td>nan                      </td><td>nan       </td><td>nan                   </td><td>nan                   </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1,692,919,134</i></td><td>1635721458409799680</td><td>b'Gaia DR2 6917528997577384320'</td><td>6917528997577384320</td><td>776446853     </td><td>2015.5     </td><td>315.00363653770665</td><td>0.5569226827403532  </td><td>-0.006758168913672078</td><td>0.2820440565211547 </td><td>1.9776835145839613 </td><td>0.4707730790922877 </td><td>4.2009273            </td><td>10.168637963656453</td><td>1.3243511199805955 </td><td>-4.6319503374116335</td><td>0.7670280680975615 </td><td>-0.7069446999999999</td><td>-0.3524638        </td><td>-0.7288846    </td><td>0.64234614     </td><td>0.6655390999999999  </td><td>0.64305264          </td><td>-0.8681120000000001</td><td>0.35158044          </td><td>-0.5439387           </td><td>-0.6995311          </td><td>267                   </td><td>0                     </td><td>267                        </td><td>0                         </td><td>5.658867            </td><td>413.15482000000003   </td><td>0.7578628201652942        </td><td>2.9604550451112943            </td><td>31                         </td><td>False                     </td><td>0.34310368             </td><td>1.3329285827339423         </td><td>0.05324715704124628              </td><td>-0.18852596           </td><td>31                                </td><td>7                        </td><td>1.3650335                </td><td>0                          </td><td>33                    </td><td>False              </td><td>286           </td><td>691.5784446136888 </td><td>1.5703237685944336      </td><td>440.405                      </td><td>18.588762        </td><td>0              </td><td>nan                </td><td>nan                      </td><td>nan                           </td><td>nan               </td><td>0              </td><td>nan                </td><td>nan                      </td><td>nan                           </td><td>nan               </td><td>nan                       </td><td>2               </td><td>nan      </td><td>nan               </td><td>nan               </td><td>nan              </td><td>nan                    </td><td>0               </td><td>nan               </td><td>nan               </td><td>nan               </td><td>b'NOT_AVAILABLE'    </td><td>48.91384657658588 </td><td>-28.266484088273092</td><td>317.4657484276085 </td><td>16.32853338725998  </td><td>nan          </td><td>nan       </td><td>nan                    </td><td>nan                    </td><td>nan      </td><td>nan                   </td><td>nan                   </td><td>nan              </td><td>nan                           </td><td>nan                           </td><td>nan          </td><td>nan         </td><td>nan                      </td><td>nan                      </td><td>nan       </td><td>nan                   </td><td>nan                   </td></tr>\n",
       "</tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "#              solution_id          designation                      source_id            random_index    ref_epoch    ra                  ra_error              dec                    dec_error            parallax             parallax_error       parallax_over_error    pmra                pmra_error           pmdec                pmdec_error          ra_dec_corr          ra_parallax_corr    ra_pmra_corr    ra_pmdec_corr    dec_parallax_corr     dec_pmra_corr         dec_pmdec_corr       parallax_pmra_corr    parallax_pmdec_corr    pmra_pmdec_corr       astrometric_n_obs_al    astrometric_n_obs_ac    astrometric_n_good_obs_al    astrometric_n_bad_obs_al    astrometric_gof_al    astrometric_chi2_al    astrometric_excess_noise    astrometric_excess_noise_sig    astrometric_params_solved    astrometric_primary_flag    astrometric_weight_al    astrometric_pseudo_colour    astrometric_pseudo_colour_error    mean_varpi_factor_al    astrometric_matched_observations    visibility_periods_used    astrometric_sigma5d_max    frame_rotator_object_type    matched_observations    duplicated_source    phot_g_n_obs    phot_g_mean_flux    phot_g_mean_flux_error    phot_g_mean_flux_over_error    phot_g_mean_mag    phot_bp_n_obs    phot_bp_mean_flux    phot_bp_mean_flux_error    phot_bp_mean_flux_over_error    phot_bp_mean_mag    phot_rp_n_obs    phot_rp_mean_flux    phot_rp_mean_flux_error    phot_rp_mean_flux_over_error    phot_rp_mean_mag    phot_bp_rp_excess_factor    phot_proc_mode    bp_rp      bp_g                g_rp                radial_velocity    radial_velocity_error    rv_nb_transits    rv_template_teff    rv_template_logg    rv_template_fe_h    phot_variable_flag    l                   b                    ecl_lon             ecl_lat              priam_flags    teff_val    teff_percentile_lower    teff_percentile_upper    a_g_val    a_g_percentile_lower    a_g_percentile_upper    e_bp_min_rp_val    e_bp_min_rp_percentile_lower    e_bp_min_rp_percentile_upper    flame_flags    radius_val    radius_percentile_lower    radius_percentile_upper    lum_val     lum_percentile_lower    lum_percentile_upper\n",
       "0              1635721458409799680  b'Gaia DR2 4295806720'           4295806720           833719442       2015.5       44.9961536841596    0.119381727827906     0.005615806210679649   0.12287249077395065  0.07144782399869501  0.16248493485095816  0.43971968             11.733411429340324  0.2431241681877592   -4.7759340851709     0.2389884371856387   0.022670548          0.27376112          -0.061221834    0.09342154       -0.43380169999999996  -0.10258209           -0.23457742          0.2862106             0.24838115             0.30606467            107                     0                       106                          1                           1.6358627000000001    125.30832              0.0                         0.0                             31                           False                       1.6281219999999998       1.6129292688600716           0.03975095740667449                0.026966427             13                                  10                         0.25016737                 0                            13                      False                103             1635.9507708728468  2.7757613305963007        589.3701                       17.65394           10               785.6408778060331    8.304744041442405          94.601456                       18.113329           11               1205.3932347369573   12.695619867587247         94.9456                         17.059097           1.2170502                   0                 1.0542316  0.45938873          0.5948429000000001  nan                nan                      0                 nan                 nan                 nan                 b'NOT_AVAILABLE'      176.9510737567222   -48.901521688994805  42.5337243367526    -16.32957311107743   nan            nan         nan                      nan                      nan        nan                     nan                     nan                nan                             nan                             nan            nan           nan                        nan                        nan         nan                     nan\n",
       "1              1635721458409799680  b'Gaia DR2 34361129088'          34361129088          1253687186      2015.5       45.00431616420765   0.13221516031053107   0.021045032689712983   0.15033009946029466  3.48677407917816     0.1943677537725032   17.939056              30.2997273525487    0.2890571540060363   20.102047674607906   0.2904121164006919   0.06490505           0.10328879          -3.8125843e-05  0.010977124      -0.5181503            -0.15682727           -0.25213727          0.25715247            0.36133286             0.21847394            97                      0                       97                           0                           3.1044097             139.97816              0.4393295485806768          2.2560181660871423              31                           False                       1.285051                 1.3322381786391089           0.043729691466259976               0.030602371             11                                  9                          0.29393765                 0                            11                      False                96              1712.9128925457007  3.0338739347619077        564.59595                      17.604027          11               397.3368347119427    13.369227259151073         29.720254999999998              18.85349            10               2155.4795941459947   8.25350128363993           261.15942                       16.428060000000002  1.4903364                   0                 2.4254303  1.249464            1.1759663           nan                nan                      0                 nan                 nan                 nan                 b'NOT_AVAILABLE'      176.94278716312405  -48.88493841774036   42.54656815575859   -16.317213719979975  nan            nan         nan                      nan                      nan        nan                     nan                     nan                nan                             nan                             nan            nan           nan                        nan                        nan         nan                     nan\n",
       "2              1635721458409799680  b'Gaia DR2 38655544960'          38655544960          1168973894      2015.5       45.004974244984105  0.029723176168001464  0.019877000365797717   0.0398615194906984   3.1212565825574363   0.04667520041451068  66.87184               29.669773387717747  0.07106567711614904  19.225962799772443   0.08279741152631212  0.11690165           0.2090516           -0.14794418     -0.082815714     -0.6151166            -0.4523399            -0.59776425          0.45273238            0.47702566             0.595477              104                     0                       104                          0                           -2.2898765            69.61933               0.0                         0.0                             31                           False                       54.20531999999999        1.5148504032402288           0.010003998099121137               0.07058261              12                                  9                          0.10163828                 0                            12                      False                103             41605.42089500058   18.392505474272053        2262.0854                      14.140491          11               17692.585419434203   53.957682875030116         327.89743                       14.731910000000001  11               34351.87449020634    58.427462958732775         587.94055                       13.422044           1.2509058000000002          0                 1.309866   0.5914191999999999  0.71844673          nan                nan                      0                 nan                 nan                 nan                 b'NOT_AVAILABLE'      176.94476069003898  -48.88527495232597   42.54686709098933   -16.318523323705843  100001.0       4962.0      4770.505                 5050.6665                0.032      0.0149                  0.2091                  0.016              0.0069                          0.0728                          200111.0       0.5863995     0.5659911999999999         0.63442224                 0.18780576  0.18156888              0.19404264\n",
       "3              1635721458409799680  b'Gaia DR2 309238066432'         309238066432         716364491       2015.5       44.99503703932583   0.3748451704441453    0.03815183599451371    0.354580932399439    1.5788410668677395   0.4509078829430168   3.5014714999999996     0.9185563546406772  0.8071335238976993   -0.4685586426340295  0.7201817396537079   0.042778816          0.14737031          -0.08400111     0.071659945      -0.175486             0.009628623000000001  -0.06346788          0.19779278            0.17691185             0.061723847000000005  114                     0                       114                          0                           -0.38584504           102.75944              0.0                         0.0                             31                           False                       0.1383114                1.2159144402017843           0.1151187960793006                 -0.07122756             13                                  10                         0.71777946                 0                            13                      False                114             263.32165329152957  1.644274128985754         160.14462                      19.63715           9                50.62248230415713    4.981187273921231          10.162734                       21.090529999999998  9                355.4098452181598    7.532196715416053          47.185417                       18.385096           1.5419633                   0                 2.7054348  1.4533806           1.2520542           nan                nan                      0                 nan                 nan                 nan                 b'NOT_AVAILABLE'      176.91426520135354  -48.87974729251865   42.54254808202412   -16.29813865533474   nan            nan         nan                      nan                      nan        nan                     nan                     nan                nan                             nan                             nan            nan           nan                        nan                        nan         nan                     nan\n",
       "4              1635721458409799680  b'Gaia DR2 343597448960'         343597448960         1007197339      2015.5       44.963895325304286  0.1672591368280593    0.04359518482272568    0.15843084907464913  0.1124232337595906   0.19677095501039435  0.5713406              6.778646355438693   0.34015943821418143  -1.5922073291150058  0.3142620551370774   0.095711425          0.25192115          -0.09463473     0.11687218       -0.14148766           0.10662418            0.001552241          0.1539189             0.0099432925           0.1900829             114                     0                       111                          3                           0.7612909000000001    116.762924             0.4379146032596523          1.164799959704128               31                           False                       0.7568838999999999       1.5231059896314436           0.0485359898688584                 0.009498954             13                                  9                          0.31823537                 0                            13                      False                109             1037.4128672255997  2.2948097285863445        452.06924000000004             18.148487          9                446.11647691960206   12.472760208872558         35.76726                        18.727767999999998  10               851.5124585934102    10.580999260922557         80.47561999999999               17.436443           1.2508317                   0                 1.2913246  0.57928085          0.71204376          nan                nan                      0                 nan                 nan                 nan                 b'NOT_AVAILABLE'      176.8754231026413   -48.89837989670807   42.513191444633726  -16.28380551789907   nan            nan         nan                      nan                      nan        nan                     nan                     nan                nan                             nan                             nan            nan           nan                        nan                        nan         nan                     nan\n",
       "...            ...                  ...                              ...                  ...             ...          ...                 ...                   ...                    ...                  ...                  ...                  ...                    ...                 ...                  ...                  ...                  ...                  ...                 ...             ...              ...                   ...                   ...                  ...                   ...                    ...                   ...                     ...                     ...                          ...                         ...                   ...                    ...                         ...                             ...                          ...                         ...                      ...                          ...                                ...                     ...                                 ...                        ...                        ...                          ...                     ...                  ...             ...                 ...                       ...                            ...                ...              ...                  ...                        ...                             ...                 ...              ...                  ...                        ...                             ...                 ...                         ...               ...        ...                 ...                 ...                ...                      ...               ...                 ...                 ...                 ...                   ...                 ...                  ...                 ...                  ...            ...         ...                      ...                      ...        ...                     ...                     ...                ...                             ...                             ...            ...           ...                        ...                        ...         ...                     ...\n",
       "1,692,919,130  1635721458409799680  b'Gaia DR2 6917528963217645568'  6917528963217645568  711904833       2015.5       314.98351260118864  6.1917502919260725    -0.017961413757040568  1.9976645630944625   nan                  nan                  nan                    nan                 nan                  nan                  nan                  -0.9468261999999998  nan                 nan             nan              nan                   nan                   nan                  nan                   nan                    nan                   256                     0                       255                          1                           0.09006713            251.34973              0.0                         0.0                             3                            False                       0.035857863999999996     nan                          nan                                -0.18235932             30                                  6                          13.550334                  0                            36                      False                276             130.46916462266304  0.8370730500448316        155.86354                      20.399595          0                nan                  nan                        nan                             nan                 0                nan                  nan                        nan                             nan                 nan                         2                 nan        nan                 nan                 nan                nan                      0                 nan                 nan                 nan                 b'NOT_AVAILABLE'      48.891138199898776  -28.255063825226554  317.44227847436525  16.323719462219874   nan            nan         nan                      nan                      nan        nan                     nan                     nan                nan                             nan                             nan            nan           nan                        nan                        nan         nan                     nan\n",
       "1,692,919,131  1635721458409799680  b'Gaia DR2 6917528993281571840'  6917528993281571840  1057759634      2015.5       314.9904017564393   0.2686243051566997    -0.008367585301478679  0.13220884263955485  0.9767377244025096   0.20966425878115624  4.658580000000001      -8.789568499444613  0.6024182711252432   -9.887007450999603   0.3609798630506912   -0.71226794          -0.32785413         -0.79407966     0.67225677       0.6483722             0.66855806            -0.88509864          0.31642532            -0.57081836            -0.71771705           288                     0                       286                          2                           0.15602541            284.04306              0.10468895650873274         0.1926633779846534              31                           False                       1.5025905000000002       1.4398141313394808           0.024217901524240717               -0.18079054             33                                  7                          0.6392459                  0                            35                      False                300             1708.7844181229475  1.7183001457312599        994.4621                       17.606647          0                nan                  nan                        nan                             nan                 0                nan                  nan                        nan                             nan                 nan                         2                 nan        nan                 nan                 nan                nan                      0                 nan                 nan                 nan                 b'NOT_AVAILABLE'      48.90450543399686   -28.25599336436905   317.4520713869125   16.330873481856276   nan            nan         nan                      nan                      nan        nan                     nan                     nan                nan                             nan                             nan            nan           nan                        nan                        nan         nan                     nan\n",
       "1,692,919,132  1635721458409799680  b'Gaia DR2 6917528993281819008'  6917528993281819008  49260802        2015.5       315.00503877002456  0.9552057496355612    -0.005736736411478651  0.4779456781063856   -0.1827374708936312  0.6920683360998278   -0.26404542            -2.893619483581229  2.08879809691233     -10.430692969558967  1.3486921231345796   -0.6087746           -0.27599064         -0.81443137     0.5377084        0.5961895             0.5714225             -0.9083530000000001  0.24399203            -0.50589395            -0.5980193            262                     0                       260                          2                           0.8898790000000001    274.92728              0.0                         0.0                             31                           False                       0.15255077               1.4387809895123045           0.08102495521913795                -0.17755668             30                                  7                          2.18716                    0                            32                      False                276             334.30089812181717  1.2490521307085771        267.64367999999996             19.378021          0                nan                  nan                        nan                             nan                 0                nan                  nan                        nan                             nan                 nan                         2                 nan        nan                 nan                 nan                nan                      0                 nan                 nan                 nan                 b'NOT_AVAILABLE'      48.915662985463     -28.26715505980319   317.46745740038915  16.329098939790963   nan            nan         nan                      nan                      nan        nan                     nan                     nan                nan                             nan                             nan            nan           nan                        nan                        nan         nan                     nan\n",
       "1,692,919,133  1635721458409799680  b'Gaia DR2 6917528993283204480'  6917528993283204480  916652582       2015.5       314.9990508711522   1.0200557955731553    -0.002570580482067311  0.4785034535013264   1.1944658684106606   0.7390532046807501   1.6162108999999998     -4.969626151660421  2.3067588023833188   -3.8381494703152055  1.3348034677367284   -0.6952682           -0.19890665         -0.81487304     0.6605273        0.5953058000000001    0.6642836999999999    -0.8895016           0.19809727            -0.5282448000000001    -0.72904134           270                     9                       268                          2                           -0.077295646          260.5681               0.0                         0.0                             31                           False                       0.1274624                1.4639756577435132           0.09127171084755213                -0.18912020000000002    31                                  7                          2.3505502000000003         0                            33                      False                283             284.94374839895426  1.2279312655182504        232.05186                      19.551468          0                nan                  nan                        nan                             nan                 0                nan                  nan                        nan                             nan                 nan                         2                 nan        nan                 nan                 nan                nan                      0                 nan                 nan                 nan                 b'NOT_AVAILABLE'      48.91521924800499   -28.26039290592401   317.4624588295149   16.333881134855314   nan            nan         nan                      nan                      nan        nan                     nan                     nan                nan                             nan                             nan            nan           nan                        nan                        nan         nan                     nan\n",
       "1,692,919,134  1635721458409799680  b'Gaia DR2 6917528997577384320'  6917528997577384320  776446853       2015.5       315.00363653770665  0.5569226827403532    -0.006758168913672078  0.2820440565211547   1.9776835145839613   0.4707730790922877   4.2009273              10.168637963656453  1.3243511199805955   -4.6319503374116335  0.7670280680975615   -0.7069446999999999  -0.3524638          -0.7288846      0.64234614       0.6655390999999999    0.64305264            -0.8681120000000001  0.35158044            -0.5439387             -0.6995311            267                     0                       267                          0                           5.658867              413.15482000000003     0.7578628201652942          2.9604550451112943              31                           False                       0.34310368               1.3329285827339423           0.05324715704124628                -0.18852596             31                                  7                          1.3650335                  0                            33                      False                286             691.5784446136888   1.5703237685944336        440.405                        18.588762          0                nan                  nan                        nan                             nan                 0                nan                  nan                        nan                             nan                 nan                         2                 nan        nan                 nan                 nan                nan                      0                 nan                 nan                 nan                 b'NOT_AVAILABLE'      48.91384657658588   -28.266484088273092  317.4657484276085   16.32853338725998    nan            nan         nan                      nan                      nan        nan                     nan                     nan                nan                             nan                             nan            nan           nan                        nan                        nan         nan                     nan"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_gaia"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Open the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:07:02.670129Z",
     "start_time": "2019-07-13T14:07:02.650375Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of samples in the data: 1,173,057,927\n"
     ]
    }
   ],
   "source": [
    "# Opens the data\n",
    "df = vaex.open('/data/yellow_taxi_2009_2015_f32.hdf5')\n",
    "\n",
    "# Check length\n",
    "print(f'Number of samples in the data: {len(df):,}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:07:12.307145Z",
     "start_time": "2019-07-13T14:07:12.271983Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th>#                                        </th><th>vendor_id  </th><th>pickup_datetime              </th><th>dropoff_datetime             </th><th>passenger_count  </th><th>payment_type  </th><th>trip_distance     </th><th>pickup_longitude  </th><th>pickup_latitude   </th><th>rate_code  </th><th>store_and_fwd_flag  </th><th>dropoff_longitude  </th><th>dropoff_latitude  </th><th>fare_amount       </th><th>surcharge  </th><th>mta_tax  </th><th>tip_amount        </th><th>tolls_amount  </th><th>total_amount      </th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td><i style='opacity: 0.6'>0</i>            </td><td>VTS        </td><td>2009-01-04 02:52:00.000000000</td><td>2009-01-04 03:02:00.000000000</td><td>1                </td><td>CASH          </td><td>2.630000114440918 </td><td>-73.99195861816406</td><td>40.72156524658203 </td><td>nan        </td><td>nan                 </td><td>-73.99380493164062 </td><td>40.6959228515625  </td><td>8.899999618530273 </td><td>0.5        </td><td>nan      </td><td>0.0               </td><td>0.0           </td><td>9.399999618530273 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1</i>            </td><td>VTS        </td><td>2009-01-04 03:31:00.000000000</td><td>2009-01-04 03:38:00.000000000</td><td>3                </td><td>Credit        </td><td>4.550000190734863 </td><td>-73.98210144042969</td><td>40.736289978027344</td><td>nan        </td><td>nan                 </td><td>-73.95584869384766 </td><td>40.768028259277344</td><td>12.100000381469727</td><td>0.5        </td><td>nan      </td><td>2.0               </td><td>0.0           </td><td>14.600000381469727</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>2</i>            </td><td>VTS        </td><td>2009-01-03 15:43:00.000000000</td><td>2009-01-03 15:57:00.000000000</td><td>5                </td><td>Credit        </td><td>10.350000381469727</td><td>-74.0025863647461 </td><td>40.73974609375    </td><td>nan        </td><td>nan                 </td><td>-73.86997985839844 </td><td>40.770225524902344</td><td>23.700000762939453</td><td>0.0        </td><td>nan      </td><td>4.739999771118164 </td><td>0.0           </td><td>28.440000534057617</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>3</i>            </td><td>DDS        </td><td>2009-01-01 20:52:58.000000000</td><td>2009-01-01 21:14:00.000000000</td><td>1                </td><td>CREDIT        </td><td>5.0               </td><td>-73.9742660522461 </td><td>40.79095458984375 </td><td>nan        </td><td>nan                 </td><td>-73.9965591430664  </td><td>40.731849670410156</td><td>14.899999618530273</td><td>0.5        </td><td>nan      </td><td>3.049999952316284 </td><td>0.0           </td><td>18.450000762939453</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>4</i>            </td><td>DDS        </td><td>2009-01-24 16:18:23.000000000</td><td>2009-01-24 16:24:56.000000000</td><td>1                </td><td>CASH          </td><td>0.4000000059604645</td><td>-74.00157928466797</td><td>40.719383239746094</td><td>nan        </td><td>nan                 </td><td>-74.00837707519531 </td><td>40.7203483581543  </td><td>3.700000047683716 </td><td>0.0        </td><td>nan      </td><td>0.0               </td><td>0.0           </td><td>3.700000047683716 </td></tr>\n",
       "<tr><td>...                                      </td><td>...        </td><td>...                          </td><td>...                          </td><td>...              </td><td>...           </td><td>...               </td><td>...               </td><td>...               </td><td>...        </td><td>...                 </td><td>...                </td><td>...               </td><td>...               </td><td>...        </td><td>...      </td><td>...               </td><td>...           </td><td>...               </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1,173,057,922</i></td><td>VTS        </td><td>2015-12-31 23:59:56.000000000</td><td>2016-01-01 00:08:18.000000000</td><td>5                </td><td>1             </td><td>1.2000000476837158</td><td>-73.99381256103516</td><td>40.72087097167969 </td><td>1.0        </td><td>0.0                 </td><td>-73.98621368408203 </td><td>40.722469329833984</td><td>7.5               </td><td>0.5        </td><td>0.5      </td><td>1.7599999904632568</td><td>0.0           </td><td>10.5600004196167  </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1,173,057,923</i></td><td>CMT        </td><td>2015-12-31 23:59:58.000000000</td><td>2016-01-01 00:05:19.000000000</td><td>2                </td><td>2             </td><td>2.0               </td><td>-73.96527099609375</td><td>40.76028060913086 </td><td>1.0        </td><td>0.0                 </td><td>-73.93951416015625 </td><td>40.75238800048828 </td><td>7.5               </td><td>0.5        </td><td>0.5      </td><td>0.0               </td><td>0.0           </td><td>8.800000190734863 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1,173,057,924</i></td><td>CMT        </td><td>2015-12-31 23:59:59.000000000</td><td>2016-01-01 00:12:55.000000000</td><td>2                </td><td>2             </td><td>3.799999952316284 </td><td>-73.98729705810547</td><td>40.739078521728516</td><td>1.0        </td><td>0.0                 </td><td>-73.9886703491211  </td><td>40.69329833984375 </td><td>13.5              </td><td>0.5        </td><td>0.5      </td><td>0.0               </td><td>0.0           </td><td>14.800000190734863</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1,173,057,925</i></td><td>VTS        </td><td>2015-12-31 23:59:59.000000000</td><td>2016-01-01 00:10:26.000000000</td><td>1                </td><td>2             </td><td>1.9600000381469727</td><td>-73.99755859375   </td><td>40.72569274902344 </td><td>1.0        </td><td>0.0                 </td><td>-74.01712036132812 </td><td>40.705322265625   </td><td>8.5               </td><td>0.5        </td><td>0.5      </td><td>0.0               </td><td>0.0           </td><td>9.800000190734863 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1,173,057,926</i></td><td>VTS        </td><td>2015-12-31 23:59:59.000000000</td><td>2016-01-01 00:21:30.000000000</td><td>1                </td><td>1             </td><td>1.059999942779541 </td><td>-73.9843978881836 </td><td>40.76725769042969 </td><td>1.0        </td><td>0.0                 </td><td>-73.99098205566406 </td><td>40.76057052612305 </td><td>13.5              </td><td>0.5        </td><td>0.5      </td><td>2.9600000381469727</td><td>0.0           </td><td>17.760000228881836</td></tr>\n",
       "</tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "#              vendor_id    pickup_datetime                dropoff_datetime               passenger_count    payment_type    trip_distance       pickup_longitude    pickup_latitude     rate_code    store_and_fwd_flag    dropoff_longitude    dropoff_latitude    fare_amount         surcharge    mta_tax    tip_amount          tolls_amount    total_amount\n",
       "0              VTS          2009-01-04 02:52:00.000000000  2009-01-04 03:02:00.000000000  1                  CASH            2.630000114440918   -73.99195861816406  40.72156524658203   nan          nan                   -73.99380493164062   40.6959228515625    8.899999618530273   0.5          nan        0.0                 0.0             9.399999618530273\n",
       "1              VTS          2009-01-04 03:31:00.000000000  2009-01-04 03:38:00.000000000  3                  Credit          4.550000190734863   -73.98210144042969  40.736289978027344  nan          nan                   -73.95584869384766   40.768028259277344  12.100000381469727  0.5          nan        2.0                 0.0             14.600000381469727\n",
       "2              VTS          2009-01-03 15:43:00.000000000  2009-01-03 15:57:00.000000000  5                  Credit          10.350000381469727  -74.0025863647461   40.73974609375      nan          nan                   -73.86997985839844   40.770225524902344  23.700000762939453  0.0          nan        4.739999771118164   0.0             28.440000534057617\n",
       "3              DDS          2009-01-01 20:52:58.000000000  2009-01-01 21:14:00.000000000  1                  CREDIT          5.0                 -73.9742660522461   40.79095458984375   nan          nan                   -73.9965591430664    40.731849670410156  14.899999618530273  0.5          nan        3.049999952316284   0.0             18.450000762939453\n",
       "4              DDS          2009-01-24 16:18:23.000000000  2009-01-24 16:24:56.000000000  1                  CASH            0.4000000059604645  -74.00157928466797  40.719383239746094  nan          nan                   -74.00837707519531   40.7203483581543    3.700000047683716   0.0          nan        0.0                 0.0             3.700000047683716\n",
       "...            ...          ...                            ...                            ...                ...             ...                 ...                 ...                 ...          ...                   ...                  ...                 ...                 ...          ...        ...                 ...             ...\n",
       "1,173,057,922  VTS          2015-12-31 23:59:56.000000000  2016-01-01 00:08:18.000000000  5                  1               1.2000000476837158  -73.99381256103516  40.72087097167969   1.0          0.0                   -73.98621368408203   40.722469329833984  7.5                 0.5          0.5        1.7599999904632568  0.0             10.5600004196167\n",
       "1,173,057,923  CMT          2015-12-31 23:59:58.000000000  2016-01-01 00:05:19.000000000  2                  2               2.0                 -73.96527099609375  40.76028060913086   1.0          0.0                   -73.93951416015625   40.75238800048828   7.5                 0.5          0.5        0.0                 0.0             8.800000190734863\n",
       "1,173,057,924  CMT          2015-12-31 23:59:59.000000000  2016-01-01 00:12:55.000000000  2                  2               3.799999952316284   -73.98729705810547  40.739078521728516  1.0          0.0                   -73.9886703491211    40.69329833984375   13.5                0.5          0.5        0.0                 0.0             14.800000190734863\n",
       "1,173,057,925  VTS          2015-12-31 23:59:59.000000000  2016-01-01 00:10:26.000000000  1                  2               1.9600000381469727  -73.99755859375     40.72569274902344   1.0          0.0                   -74.01712036132812   40.705322265625     8.5                 0.5          0.5        0.0                 0.0             9.800000190734863\n",
       "1,173,057,926  VTS          2015-12-31 23:59:59.000000000  2016-01-01 00:21:30.000000000  1                  1               1.059999942779541   -73.9843978881836   40.76725769042969   1.0          0.0                   -73.99098205566406   40.76057052612305   13.5                0.5          0.5        2.9600000381469727  0.0             17.760000228881836"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# View a portion of the dataset\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Split the data into train & test sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:07:27.380920Z",
     "start_time": "2019-07-13T14:07:27.369542Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of samples in the training set: 1,026,944,937\n",
      "Number of samples in the test set:       146,112,990\n"
     ]
    }
   ],
   "source": [
    "# Train / test split (by date)\n",
    "df_train = df[:1_026_944_937]\n",
    "df_test = df[1_026_944_937:]\n",
    "\n",
    "print(f'Number of samples in the training set: {len(df_train):,}')\n",
    "print(f'Number of samples in the test set:       {len(df_test):,}')\n",
    "\n",
    "# Check if the lengths of the datasets match\n",
    "assert len(df) == len(df_test) + len(df_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Basic view in the contents of the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:09:04.132513Z",
     "start_time": "2019-07-13T14:07:39.379824Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vendor_id</th>\n",
       "      <th>pickup_datetime</th>\n",
       "      <th>dropoff_datetime</th>\n",
       "      <th>passenger_count</th>\n",
       "      <th>payment_type</th>\n",
       "      <th>trip_distance</th>\n",
       "      <th>pickup_longitude</th>\n",
       "      <th>pickup_latitude</th>\n",
       "      <th>rate_code</th>\n",
       "      <th>store_and_fwd_flag</th>\n",
       "      <th>dropoff_longitude</th>\n",
       "      <th>dropoff_latitude</th>\n",
       "      <th>fare_amount</th>\n",
       "      <th>surcharge</th>\n",
       "      <th>mta_tax</th>\n",
       "      <th>tip_amount</th>\n",
       "      <th>tolls_amount</th>\n",
       "      <th>total_amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>dtype</th>\n",
       "      <td>str</td>\n",
       "      <td>datetime64[ns]</td>\n",
       "      <td>datetime64[ns]</td>\n",
       "      <td>int64</td>\n",
       "      <td>str</td>\n",
       "      <td>float32</td>\n",
       "      <td>float32</td>\n",
       "      <td>float32</td>\n",
       "      <td>float32</td>\n",
       "      <td>float32</td>\n",
       "      <td>float32</td>\n",
       "      <td>float32</td>\n",
       "      <td>float32</td>\n",
       "      <td>float32</td>\n",
       "      <td>float32</td>\n",
       "      <td>float32</td>\n",
       "      <td>float32</td>\n",
       "      <td>float32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1026944937</td>\n",
       "      <td>1026944937</td>\n",
       "      <td>1026944937</td>\n",
       "      <td>1026944937</td>\n",
       "      <td>1026944937</td>\n",
       "      <td>1026944937</td>\n",
       "      <td>1026944937</td>\n",
       "      <td>1026944936</td>\n",
       "      <td>856048881</td>\n",
       "      <td>492801449</td>\n",
       "      <td>1026930442</td>\n",
       "      <td>1026937251</td>\n",
       "      <td>1026944936</td>\n",
       "      <td>1026944936</td>\n",
       "      <td>885904367</td>\n",
       "      <td>1026944936</td>\n",
       "      <td>1026944936</td>\n",
       "      <td>1026944936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NA</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>170896056</td>\n",
       "      <td>534143488</td>\n",
       "      <td>14495</td>\n",
       "      <td>7686</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>141040570</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>--</td>\n",
       "      <td>1970-01-01T00:00:09.363074997</td>\n",
       "      <td>1970-01-01T00:00:17.117798649</td>\n",
       "      <td>1.6849674628660252</td>\n",
       "      <td>--</td>\n",
       "      <td>4.2887783920701805</td>\n",
       "      <td>-72.49317243472608</td>\n",
       "      <td>39.90989106383116</td>\n",
       "      <td>1.0347555456941249</td>\n",
       "      <td>0.01978832452661883</td>\n",
       "      <td>-72.49243151212976</td>\n",
       "      <td>39.90885643799402</td>\n",
       "      <td>10.972378852412822</td>\n",
       "      <td>0.30212644001978256</td>\n",
       "      <td>0.49609965013291546</td>\n",
       "      <td>1.0442341037367946</td>\n",
       "      <td>0.16956585476496344</td>\n",
       "      <td>12.919018626881291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>--</td>\n",
       "      <td>5.36654e+16</td>\n",
       "      <td>5.36655e+16</td>\n",
       "      <td>1.32989</td>\n",
       "      <td>--</td>\n",
       "      <td>3538.44</td>\n",
       "      <td>13.1757</td>\n",
       "      <td>9.98901</td>\n",
       "      <td>0.390535</td>\n",
       "      <td>0.139272</td>\n",
       "      <td>13.112</td>\n",
       "      <td>9.98311</td>\n",
       "      <td>675.441</td>\n",
       "      <td>0.372003</td>\n",
       "      <td>0.0709658</td>\n",
       "      <td>70.4219</td>\n",
       "      <td>947.702</td>\n",
       "      <td>1166.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>--</td>\n",
       "      <td>2009-01-01T00:00:27.365015552</td>\n",
       "      <td>2009-01-01T00:00:27.365015552</td>\n",
       "      <td>0</td>\n",
       "      <td>--</td>\n",
       "      <td>-2.14748e+07</td>\n",
       "      <td>-3509.02</td>\n",
       "      <td>-3579.14</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-3579.14</td>\n",
       "      <td>-3579.14</td>\n",
       "      <td>-2.14748e+07</td>\n",
       "      <td>-19.5</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1.67772e+06</td>\n",
       "      <td>-2.14748e+07</td>\n",
       "      <td>-2.14748e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>--</td>\n",
       "      <td>2014-12-31T23:59:54.563395584</td>\n",
       "      <td>2015-01-01T00:59:27.976185856</td>\n",
       "      <td>255</td>\n",
       "      <td>--</td>\n",
       "      <td>1.62016e+07</td>\n",
       "      <td>3570.22</td>\n",
       "      <td>3577.14</td>\n",
       "      <td>252</td>\n",
       "      <td>2</td>\n",
       "      <td>3460.43</td>\n",
       "      <td>3577.14</td>\n",
       "      <td>158996</td>\n",
       "      <td>854.5</td>\n",
       "      <td>1311.22</td>\n",
       "      <td>938.02</td>\n",
       "      <td>5510.07</td>\n",
       "      <td>685908</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        vendor_id                pickup_datetime  \\\n",
       "dtype         str                 datetime64[ns]   \n",
       "count  1026944937                     1026944937   \n",
       "NA              0                              0   \n",
       "mean           --  1970-01-01T00:00:09.363074997   \n",
       "std            --                    5.36654e+16   \n",
       "min            --  2009-01-01T00:00:27.365015552   \n",
       "max            --  2014-12-31T23:59:54.563395584   \n",
       "\n",
       "                    dropoff_datetime     passenger_count payment_type  \\\n",
       "dtype                 datetime64[ns]               int64          str   \n",
       "count                     1026944937          1026944937   1026944937   \n",
       "NA                                 0                   0            0   \n",
       "mean   1970-01-01T00:00:17.117798649  1.6849674628660252           --   \n",
       "std                      5.36655e+16             1.32989           --   \n",
       "min    2009-01-01T00:00:27.365015552                   0           --   \n",
       "max    2015-01-01T00:59:27.976185856                 255           --   \n",
       "\n",
       "            trip_distance    pickup_longitude    pickup_latitude  \\\n",
       "dtype             float32             float32            float32   \n",
       "count          1026944937          1026944937         1026944936   \n",
       "NA                      0                   0                  1   \n",
       "mean   4.2887783920701805  -72.49317243472608  39.90989106383116   \n",
       "std               3538.44             13.1757            9.98901   \n",
       "min          -2.14748e+07            -3509.02           -3579.14   \n",
       "max           1.62016e+07             3570.22            3577.14   \n",
       "\n",
       "                rate_code   store_and_fwd_flag   dropoff_longitude  \\\n",
       "dtype             float32              float32             float32   \n",
       "count           856048881            492801449          1026930442   \n",
       "NA              170896056            534143488               14495   \n",
       "mean   1.0347555456941249  0.01978832452661883  -72.49243151212976   \n",
       "std              0.390535             0.139272              13.112   \n",
       "min                     0                    0            -3579.14   \n",
       "max                   252                    2             3460.43   \n",
       "\n",
       "        dropoff_latitude         fare_amount            surcharge  \\\n",
       "dtype            float32             float32              float32   \n",
       "count         1026937251          1026944936           1026944936   \n",
       "NA                  7686                   1                    1   \n",
       "mean   39.90885643799402  10.972378852412822  0.30212644001978256   \n",
       "std              9.98311             675.441             0.372003   \n",
       "min             -3579.14        -2.14748e+07                -19.5   \n",
       "max              3577.14              158996                854.5   \n",
       "\n",
       "                   mta_tax          tip_amount         tolls_amount  \\\n",
       "dtype              float32             float32              float32   \n",
       "count            885904367          1026944936           1026944936   \n",
       "NA               141040570                   1                    1   \n",
       "mean   0.49609965013291546  1.0442341037367946  0.16956585476496344   \n",
       "std              0.0709658             70.4219              947.702   \n",
       "min                     -1        -1.67772e+06         -2.14748e+07   \n",
       "max                1311.22              938.02              5510.07   \n",
       "\n",
       "             total_amount  \n",
       "dtype             float32  \n",
       "count          1026944936  \n",
       "NA                      1  \n",
       "mean   12.919018626881291  \n",
       "std               1166.23  \n",
       "min          -2.14748e+07  \n",
       "max                685908  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Basic description about the training dataset\n",
    "df_train.describe()\n",
    "# 9 min"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Remove missing data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:10:46.793843Z",
     "start_time": "2019-07-13T14:10:46.482416Z"
    }
   },
   "outputs": [],
   "source": [
    "# Drop NANs\n",
    "df_train = df_train.dropna(column_names=['dropoff_latitude', 'dropoff_longitude', 'pickup_latitude'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Abnormal number of passengers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:11:37.631584Z",
     "start_time": "2019-07-13T14:11:36.198996Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################]:  100.00% elapsed time  :        1s =  0.0m =  0.0h \n",
      " "
     ]
    },
    {
     "data": {
      "text/plain": [
       "1      709330188\n",
       "2      151963187\n",
       "5       73984911\n",
       "3       45300783\n",
       "4       22002415\n",
       "6       20490752\n",
       "0        3870557\n",
       "208         1515\n",
       "7            196\n",
       "9            183\n",
       "8            132\n",
       "49            26\n",
       "10            17\n",
       "255           10\n",
       "129            7\n",
       "213            4\n",
       "250            3\n",
       "65             3\n",
       "15             2\n",
       "58             2\n",
       "33             2\n",
       "169            1\n",
       "37             1\n",
       "36             1\n",
       "34             1\n",
       "25             1\n",
       "19             1\n",
       "17             1\n",
       "193            1\n",
       "13             1\n",
       "         ...    \n",
       "223            1\n",
       "225            1\n",
       "229            1\n",
       "232            1\n",
       "247            1\n",
       "249            1\n",
       "38             1\n",
       "51             1\n",
       "177            1\n",
       "165            1\n",
       "164            1\n",
       "163            1\n",
       "160            1\n",
       "158            1\n",
       "155            1\n",
       "141            1\n",
       "137            1\n",
       "134            1\n",
       "133            1\n",
       "125            1\n",
       "113            1\n",
       "97             1\n",
       "91             1\n",
       "84             1\n",
       "254            1\n",
       "69             1\n",
       "66             1\n",
       "61             1\n",
       "53             1\n",
       "70             1\n",
       "Length: 62, dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Number of passengers\n",
    "df_train.passenger_count.value_counts(progress=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:11:55.481794Z",
     "start_time": "2019-07-13T14:11:55.050785Z"
    }
   },
   "outputs": [],
   "source": [
    "# Filter abnormal number of passengers\n",
    "df_train = df_train[(df_train.passenger_count>0) & (df_train.passenger_count<7)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Clean up distance values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:12:03.837263Z",
     "start_time": "2019-07-13T14:12:00.223513Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,4))\n",
    "df_train.plot1d('trip_distance', limits='minmax', f='log1p')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:12:19.270182Z",
     "start_time": "2019-07-13T14:12:18.271051Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(6920779)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# How many trips have 0.0 distance?\n",
    "(df_train.trip_distance==0).astype('int').sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:12:29.512859Z",
     "start_time": "2019-07-13T14:12:29.197480Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "16201631.0 miles.\n",
      "This is 67.8 times larger than the distance between the Earth and the Moon!\n",
      "or\n",
      "This is 0.5 the distance to Mars!\n"
     ]
    }
   ],
   "source": [
    "# What is the largest distance?\n",
    "_ = df_train.trip_distance.max()\n",
    "\n",
    "print(_, 'miles.')\n",
    "\n",
    "print('This is %3.1f times larger than the distance between the Earth and the Moon!' % (_ / 238_900))\n",
    "print('or')\n",
    "print('This is %1.1f the distance to Mars!' % (_ / 33_900_000))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:12:43.212322Z",
     "start_time": "2019-07-13T14:12:42.456397Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,4))\n",
    "df_train.plot1d('trip_distance', limits=[0, 20], f=None)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:12:56.448814Z",
     "start_time": "2019-07-13T14:12:56.138462Z"
    }
   },
   "outputs": [],
   "source": [
    "# Filter negative and too large distances\n",
    "df_train = df_train[(df_train.trip_distance>0) & (df_train.trip_distance<10)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What _is_ New York City really?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:13:05.414528Z",
     "start_time": "2019-07-13T14:13:01.467287Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "08ea61fe0db4470abc1f2bd535d69651",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "PlotTemplate(components={'main-widget': VBox(children=(VBox(children=(Figure(axes=[Axis(scale=LinearScale(allo…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Interactively plot the pickup locations\n",
    "df_train.plot_widget(df_train.pickup_longitude, \n",
    "                     df_train.pickup_latitude, \n",
    "                     shape=512, \n",
    "                     f='log1p', \n",
    "                     colormap='plasma', \n",
    "                     limits='minmax')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:14:10.158294Z",
     "start_time": "2019-07-13T14:14:10.155842Z"
    }
   },
   "outputs": [],
   "source": [
    "# Define the NYC boundaries\n",
    "long_min = -74.05\n",
    "long_max = -73.75\n",
    "lat_min = 40.58\n",
    "lat_max = 40.90"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:14:13.454774Z",
     "start_time": "2019-07-13T14:14:13.135786Z"
    }
   },
   "outputs": [],
   "source": [
    "# Make a selection based on the boundaries\n",
    "df_train = df_train[(df_train.pickup_longitude > long_min)  & (df_train.pickup_longitude < long_max) & \\\n",
    "        (df_train.pickup_latitude > lat_min)    & (df_train.pickup_latitude < lat_max) & \\\n",
    "        (df_train.dropoff_longitude > long_min) & (df_train.dropoff_longitude < long_max) & \\\n",
    "        (df_train.dropoff_latitude > lat_min)   & (df_train.dropoff_latitude < lat_max)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create some features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:14:24.145658Z",
     "start_time": "2019-07-13T14:14:20.303247Z"
    }
   },
   "outputs": [],
   "source": [
    "# Speed (miles per hour)\n",
    "df_train['trip_speed_mph'] = df_train.trip_distance / ((df_train.dropoff_datetime - df_train.pickup_datetime) / np.timedelta64(1, 'h'))\n",
    "\n",
    "# Time in transit (minutes)\n",
    "df_train['trip_duration_min'] = (df_train.dropoff_datetime - df_train.pickup_datetime) / np.timedelta64(1, 'm')\n",
    "\n",
    "# fare divided by distance\n",
    "df_train['fare_by_distance'] = (df_train.fare_amount / df_train.trip_distance).jit_numba()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### More filters: Trip duration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:14:47.012164Z",
     "start_time": "2019-07-13T14:14:35.444415Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,4))\n",
    "df_train.plot1d('trip_duration_min', f='log1p', limits='minmax')\n",
    "plt.ylabel('log(count + 1)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:15:02.496984Z",
     "start_time": "2019-07-13T14:14:59.580947Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,4))\n",
    "df_train.plot1d('trip_duration_min', f='log1p', limits=[0, 1000])\n",
    "plt.ylabel('log(count + 1)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:15:20.347530Z",
     "start_time": "2019-07-13T14:15:19.850925Z"
    }
   },
   "outputs": [],
   "source": [
    "# Filter, keep durations that are within 2 hours\n",
    "df_train = df_train[(df_train.trip_duration_min>0) & (df_train.trip_duration_min<120)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create some date/time features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:15:30.238331Z",
     "start_time": "2019-07-13T14:15:30.231528Z"
    }
   },
   "outputs": [],
   "source": [
    "# Daily activities\n",
    "df_train['pu_hour'] = df_train.pickup_datetime.dt.hour\n",
    "df_train['pu_day_of_week'] = df_train.pickup_datetime.dt.dayofweek\n",
    "df_train['pu_month'] = df_train.pickup_datetime.dt.month - 1\n",
    "df_train['pu_is_weekend'] = (df_train.pu_day_of_week>=5).astype('int')\n",
    "\n",
    "# lists to help with the labeling\n",
    "weekday_names_list = ['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun']\n",
    "month_names_list = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'July', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:15:57.212348Z",
     "start_time": "2019-07-13T14:15:41.406180Z"
    }
   },
   "outputs": [],
   "source": [
    "# Treat these columns as label/ordinal encoded values\n",
    "df_train.categorize(column='pu_hour')\n",
    "df_train.categorize(column='pu_day_of_week')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:16:08.251246Z",
     "start_time": "2019-07-13T14:15:57.213698Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Number of pick-ups per hour for a given day of the week\n",
    "df_train.plot('pu_hour', 'pu_day_of_week', colorbar=True, colormap=cm_plusmin, figsize=(15, 5))\n",
    "plt.xticks(np.arange(24), np.arange(24))\n",
    "plt.yticks(np.arange(7), weekday_names_list)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Groupby examples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:16:47.339665Z",
     "start_time": "2019-07-13T14:16:30.850706Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th>#                             </th><th>pu_hour  </th><th>tip_amount        </th><th>trip_speed_mph    </th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td><i style='opacity: 0.6'>0</i> </td><td>18       </td><td>0.8980234838056023</td><td>11.137734661477356</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1</i> </td><td>10       </td><td>0.8399432515403252</td><td>11.20425337825429 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>2</i> </td><td>12       </td><td>0.8089977525043525</td><td>10.693505721771535</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>3</i> </td><td>17       </td><td>0.8611249448688643</td><td>11.274521314883266</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>4</i> </td><td>11       </td><td>0.8204235859855356</td><td>10.926674266650382</td></tr>\n",
       "<tr><td>...                           </td><td>...      </td><td>...               </td><td>...               </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>19</i></td><td>1        </td><td>0.9736288526165442</td><td>15.98974841306951 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>20</i></td><td>3        </td><td>0.9429588809372405</td><td>17.201791052455178</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>21</i></td><td>14       </td><td>0.8012740658928521</td><td>10.669318573254484</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>22</i></td><td>6        </td><td>0.8012954928221264</td><td>17.226088364768067</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>23</i></td><td>5        </td><td>0.8713590836493932</td><td>19.91359102739638 </td></tr>\n",
       "</tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "#    pu_hour    tip_amount          trip_speed_mph\n",
       "0    18         0.8980234838056023  11.137734661477356\n",
       "1    10         0.8399432515403252  11.20425337825429\n",
       "2    12         0.8089977525043525  10.693505721771535\n",
       "3    17         0.8611249448688643  11.274521314883266\n",
       "4    11         0.8204235859855356  10.926674266650382\n",
       "...  ...        ...                 ...\n",
       "19   1          0.9736288526165442  15.98974841306951\n",
       "20   3          0.9429588809372405  17.201791052455178\n",
       "21   14         0.8012740658928521  10.669318573254484\n",
       "22   6          0.8012954928221264  17.226088364768067\n",
       "23   5          0.8713590836493932  19.91359102739638"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_per_hour = df_train.groupby(by=df_train.pu_hour).agg({'tip_amount': 'mean',\n",
    "                                                         'trip_speed_mph': 'mean',\n",
    "                                                        })\n",
    "\n",
    "# Display the grouped DataFrame\n",
    "df_per_hour"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:16:59.351414Z",
     "start_time": "2019-07-13T14:16:58.899503Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14, 5))\n",
    "\n",
    "plt.subplot(121)\n",
    "sns.barplot(x=df_per_hour.pu_hour.values, y=df_per_hour.tip_amount.values)\n",
    "plt.title('Mean tip amount')\n",
    "plt.xlabel('hour of day')\n",
    "plt.ylabel('mean tip amount')\n",
    "\n",
    "plt.subplot(122)\n",
    "sns.barplot(x=df_per_hour.pu_hour.values, y=df_per_hour.trip_speed_mph.values)\n",
    "plt.title('Mean trip speed')\n",
    "plt.xlabel('hour of day')\n",
    "plt.ylabel('mean trip speed [miles per hour]')\n",
    "\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-12T22:17:24.346153Z",
     "start_time": "2019-07-12T22:17:22.590521Z"
    }
   },
   "outputs": [],
   "source": [
    "# All the filtering, in case something went wrong\n",
    "import vaex\n",
    "import numpy as np\n",
    "import pylab as plt\n",
    "df = vaex.open('/data/yellow_taxi_2009_2015_f32.hdf5')\n",
    "magic_row_nr = 1_026_944_937\n",
    "df_train, df_test = df[:magic_row_nr], df[magic_row_nr:]\n",
    "df_train = df_train.dropna(column_names=['dropoff_latitude', 'dropoff_longitude', 'pickup_latitude'])\n",
    "df_train = df_train[(df_train.passenger_count>0) & (df_train.passenger_count<7)]\n",
    "df_train = df_train[(df_train.trip_distance>0) & (df_train.trip_distance<10)]\n",
    "# Define the NYC boundaries\n",
    "long_min = -74.05\n",
    "long_max = -73.75\n",
    "lat_min = 40.58\n",
    "lat_max = 40.90\n",
    "# Make a selection based on the boundaries\n",
    "df_train = df_train[(df_train.pickup_longitude > long_min)  & (df_train.pickup_longitude < long_max) & \\\n",
    "        (df_train.pickup_latitude > lat_min)    & (df_train.pickup_latitude < lat_max) & \\\n",
    "        (df_train.dropoff_longitude > long_min) & (df_train.dropoff_longitude < long_max) & \\\n",
    "        (df_train.dropoff_latitude > lat_min)   & (df_train.dropoff_latitude < lat_max)]\n",
    "df_train['pu_hour'] = df_train.pickup_datetime.dt.hour\n",
    "df_train['pu_day_of_week'] = df_train.pickup_datetime.dt.dayofweek\n",
    "df_train['pu_month'] = df_train.pickup_datetime.dt.month - 1\n",
    "df_train['pu_is_weekend'] = (df_train.pu_day_of_week>=5).astype('int')\n",
    "df_train['trip_speed_mph'] = df_train.trip_distance / ((df_train.dropoff_datetime - df_train.pickup_datetime) / np.timedelta64(1, 'h'))\n",
    "df_train['trip_duration_min'] = (df_train.dropoff_datetime - df_train.pickup_datetime) / np.timedelta64(1, 'm')\n",
    "df_train['fare_by_distance'] = (df_train.fare_amount / df_train.trip_distance)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Predictive modelling example: predict the likely duration of a taxi trip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:17:28.236814Z",
     "start_time": "2019-07-13T14:17:26.789273Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th>#                                      </th><th>vendor_id  </th><th>pickup_datetime              </th><th>dropoff_datetime             </th><th>passenger_count  </th><th>payment_type  </th><th>trip_distance       </th><th>pickup_longitude  </th><th>pickup_latitude   </th><th>rate_code  </th><th>store_and_fwd_flag  </th><th>dropoff_longitude  </th><th>dropoff_latitude  </th><th>fare_amount       </th><th>surcharge  </th><th>mta_tax  </th><th>tip_amount       </th><th>tolls_amount  </th><th>total_amount      </th><th>trip_speed_mph    </th><th>trip_duration_min  </th><th>fare_by_distance  </th><th>pu_hour  </th><th>pu_day_of_week  </th><th>pu_month  </th><th>pu_is_weekend  </th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td><i style='opacity: 0.6'>0</i>          </td><td>VTS        </td><td>2009-01-04 02:52:00.000000000</td><td>2009-01-04 03:02:00.000000000</td><td>1                </td><td>CASH          </td><td>2.630000114440918   </td><td>-73.99195861816406</td><td>40.72156524658203 </td><td>nan        </td><td>nan                 </td><td>-73.99380493164062 </td><td>40.6959228515625  </td><td>8.899999618530273 </td><td>0.5        </td><td>nan      </td><td>0.0              </td><td>0.0           </td><td>9.399999618530273 </td><td>15.780000686645508</td><td>10.0               </td><td>3.3840301036834717</td><td>2        </td><td>6               </td><td>0         </td><td>1              </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1</i>          </td><td>VTS        </td><td>2009-01-04 03:31:00.000000000</td><td>2009-01-04 03:38:00.000000000</td><td>3                </td><td>Credit        </td><td>4.550000190734863   </td><td>-73.98210144042969</td><td>40.736289978027344</td><td>nan        </td><td>nan                 </td><td>-73.95584869384766 </td><td>40.768028259277344</td><td>12.100000381469727</td><td>0.5        </td><td>nan      </td><td>2.0              </td><td>0.0           </td><td>14.600000381469727</td><td>39.00000163487026 </td><td>7.0                </td><td>2.6593406200408936</td><td>3        </td><td>6               </td><td>0         </td><td>1              </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>2</i>          </td><td>DDS        </td><td>2009-01-01 20:52:58.000000000</td><td>2009-01-01 21:14:00.000000000</td><td>1                </td><td>CREDIT        </td><td>5.0                 </td><td>-73.9742660522461 </td><td>40.79095458984375 </td><td>nan        </td><td>nan                 </td><td>-73.9965591430664  </td><td>40.731849670410156</td><td>14.899999618530273</td><td>0.5        </td><td>nan      </td><td>3.049999952316284</td><td>0.0           </td><td>18.450000762939453</td><td>14.263074484944532</td><td>21.033333333333335 </td><td>2.9800000190734863</td><td>20       </td><td>3               </td><td>0         </td><td>0              </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>3</i>          </td><td>DDS        </td><td>2009-01-24 16:18:23.000000000</td><td>2009-01-24 16:24:56.000000000</td><td>1                </td><td>CASH          </td><td>0.4000000059604645  </td><td>-74.00157928466797</td><td>40.719383239746094</td><td>nan        </td><td>nan                 </td><td>-74.00837707519531 </td><td>40.7203483581543  </td><td>3.700000047683716 </td><td>0.0        </td><td>nan      </td><td>0.0              </td><td>0.0           </td><td>3.700000047683716 </td><td>3.664122192004255 </td><td>6.55               </td><td>9.25              </td><td>16       </td><td>5               </td><td>0         </td><td>1              </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>4</i>          </td><td>DDS        </td><td>2009-01-16 22:35:59.000000000</td><td>2009-01-16 22:43:35.000000000</td><td>2                </td><td>CASH          </td><td>1.2000000476837158  </td><td>-73.98980712890625</td><td>40.73500442504883 </td><td>nan        </td><td>nan                 </td><td>-73.98502349853516 </td><td>40.72449493408203 </td><td>6.099999904632568 </td><td>0.5        </td><td>nan      </td><td>0.0              </td><td>0.0           </td><td>6.599999904632568 </td><td>9.473684586976702 </td><td>7.6                </td><td>5.0833330154418945</td><td>22       </td><td>4               </td><td>0         </td><td>0              </td></tr>\n",
       "<tr><td>...                                    </td><td>...        </td><td>...                          </td><td>...                          </td><td>...              </td><td>...           </td><td>...                 </td><td>...               </td><td>...               </td><td>...        </td><td>...                 </td><td>...                </td><td>...               </td><td>...               </td><td>...        </td><td>...      </td><td>...              </td><td>...           </td><td>...               </td><td>...               </td><td>...                </td><td>...               </td><td>...      </td><td>...             </td><td>...       </td><td>...            </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>947,290,814</i></td><td>VTS        </td><td>2014-12-15 19:20:00.000000000</td><td>2014-12-15 19:25:00.000000000</td><td>2                </td><td>CSH           </td><td>0.6600000262260437  </td><td>-73.95462799072266</td><td>40.77800750732422 </td><td>1.0        </td><td>nan                 </td><td>-73.96318817138672 </td><td>40.776947021484375</td><td>5.0               </td><td>1.0        </td><td>0.5      </td><td>0.0              </td><td>0.0           </td><td>6.5               </td><td>7.920000314712524 </td><td>5.0                </td><td>7.5757575035095215</td><td>19       </td><td>0               </td><td>11        </td><td>0              </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>947,290,815</i></td><td>VTS        </td><td>2014-12-15 19:21:00.000000000</td><td>2014-12-15 19:22:00.000000000</td><td>2                </td><td>CSH           </td><td>0.029999999329447746</td><td>-73.98585510253906</td><td>40.75217819213867 </td><td>1.0        </td><td>nan                 </td><td>-73.98589324951172 </td><td>40.75204849243164 </td><td>3.0               </td><td>1.0        </td><td>0.5      </td><td>0.0              </td><td>0.0           </td><td>4.5               </td><td>1.7999999597668648</td><td>1.0                </td><td>100.0             </td><td>19       </td><td>0               </td><td>11        </td><td>0              </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>947,290,816</i></td><td>VTS        </td><td>2014-12-16 01:45:00.000000000</td><td>2014-12-16 01:54:00.000000000</td><td>1                </td><td>CRD           </td><td>2.680000066757202   </td><td>-73.9609603881836 </td><td>40.79698944091797 </td><td>1.0        </td><td>nan                 </td><td>-73.98635864257812 </td><td>40.76822280883789 </td><td>10.0              </td><td>0.5        </td><td>0.5      </td><td>2.619999885559082</td><td>0.0           </td><td>13.619999885559082</td><td>17.866667111714683</td><td>9.0                </td><td>3.7313432693481445</td><td>1        </td><td>1               </td><td>11        </td><td>0              </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>947,290,817</i></td><td>VTS        </td><td>2014-12-16 02:19:00.000000000</td><td>2014-12-16 02:23:00.000000000</td><td>1                </td><td>CSH           </td><td>1.2699999809265137  </td><td>-73.98861694335938</td><td>40.748661041259766</td><td>1.0        </td><td>nan                 </td><td>-73.98274993896484 </td><td>40.76218795776367 </td><td>6.0               </td><td>0.5        </td><td>0.5      </td><td>0.0              </td><td>0.0           </td><td>7.0               </td><td>19.049999713897705</td><td>4.0                </td><td>4.724409580230713 </td><td>2        </td><td>1               </td><td>11        </td><td>0              </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>947,290,818</i></td><td>VTS        </td><td>2014-12-16 02:26:00.000000000</td><td>2014-12-16 02:28:00.000000000</td><td>1                </td><td>CSH           </td><td>1.090000033378601   </td><td>-73.98672485351562</td><td>40.75642013549805 </td><td>1.0        </td><td>nan                 </td><td>-73.9964599609375  </td><td>40.74289321899414 </td><td>5.0               </td><td>0.5        </td><td>0.5      </td><td>0.0              </td><td>0.0           </td><td>6.0               </td><td>32.70000100135803 </td><td>2.0                </td><td>4.587155818939209 </td><td>2        </td><td>1               </td><td>11        </td><td>0              </td></tr>\n",
       "</tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "#            vendor_id    pickup_datetime                dropoff_datetime               passenger_count    payment_type    trip_distance         pickup_longitude    pickup_latitude     rate_code    store_and_fwd_flag    dropoff_longitude    dropoff_latitude    fare_amount         surcharge    mta_tax    tip_amount         tolls_amount    total_amount        trip_speed_mph      trip_duration_min    fare_by_distance    pu_hour    pu_day_of_week    pu_month    pu_is_weekend\n",
       "0            VTS          2009-01-04 02:52:00.000000000  2009-01-04 03:02:00.000000000  1                  CASH            2.630000114440918     -73.99195861816406  40.72156524658203   nan          nan                   -73.99380493164062   40.6959228515625    8.899999618530273   0.5          nan        0.0                0.0             9.399999618530273   15.780000686645508  10.0                 3.3840301036834717  2          6                 0           1\n",
       "1            VTS          2009-01-04 03:31:00.000000000  2009-01-04 03:38:00.000000000  3                  Credit          4.550000190734863     -73.98210144042969  40.736289978027344  nan          nan                   -73.95584869384766   40.768028259277344  12.100000381469727  0.5          nan        2.0                0.0             14.600000381469727  39.00000163487026   7.0                  2.6593406200408936  3          6                 0           1\n",
       "2            DDS          2009-01-01 20:52:58.000000000  2009-01-01 21:14:00.000000000  1                  CREDIT          5.0                   -73.9742660522461   40.79095458984375   nan          nan                   -73.9965591430664    40.731849670410156  14.899999618530273  0.5          nan        3.049999952316284  0.0             18.450000762939453  14.263074484944532  21.033333333333335   2.9800000190734863  20         3                 0           0\n",
       "3            DDS          2009-01-24 16:18:23.000000000  2009-01-24 16:24:56.000000000  1                  CASH            0.4000000059604645    -74.00157928466797  40.719383239746094  nan          nan                   -74.00837707519531   40.7203483581543    3.700000047683716   0.0          nan        0.0                0.0             3.700000047683716   3.664122192004255   6.55                 9.25                16         5                 0           1\n",
       "4            DDS          2009-01-16 22:35:59.000000000  2009-01-16 22:43:35.000000000  2                  CASH            1.2000000476837158    -73.98980712890625  40.73500442504883   nan          nan                   -73.98502349853516   40.72449493408203   6.099999904632568   0.5          nan        0.0                0.0             6.599999904632568   9.473684586976702   7.6                  5.0833330154418945  22         4                 0           0\n",
       "...          ...          ...                            ...                            ...                ...             ...                   ...                 ...                 ...          ...                   ...                  ...                 ...                 ...          ...        ...                ...             ...                 ...                 ...                  ...                 ...        ...               ...         ...\n",
       "947,290,814  VTS          2014-12-15 19:20:00.000000000  2014-12-15 19:25:00.000000000  2                  CSH             0.6600000262260437    -73.95462799072266  40.77800750732422   1.0          nan                   -73.96318817138672   40.776947021484375  5.0                 1.0          0.5        0.0                0.0             6.5                 7.920000314712524   5.0                  7.5757575035095215  19         0                 11          0\n",
       "947,290,815  VTS          2014-12-15 19:21:00.000000000  2014-12-15 19:22:00.000000000  2                  CSH             0.029999999329447746  -73.98585510253906  40.75217819213867   1.0          nan                   -73.98589324951172   40.75204849243164   3.0                 1.0          0.5        0.0                0.0             4.5                 1.7999999597668648  1.0                  100.0               19         0                 11          0\n",
       "947,290,816  VTS          2014-12-16 01:45:00.000000000  2014-12-16 01:54:00.000000000  1                  CRD             2.680000066757202     -73.9609603881836   40.79698944091797   1.0          nan                   -73.98635864257812   40.76822280883789   10.0                0.5          0.5        2.619999885559082  0.0             13.619999885559082  17.866667111714683  9.0                  3.7313432693481445  1          1                 11          0\n",
       "947,290,817  VTS          2014-12-16 02:19:00.000000000  2014-12-16 02:23:00.000000000  1                  CSH             1.2699999809265137    -73.98861694335938  40.748661041259766  1.0          nan                   -73.98274993896484   40.76218795776367   6.0                 0.5          0.5        0.0                0.0             7.0                 19.049999713897705  4.0                  4.724409580230713   2          1                 11          0\n",
       "947,290,818  VTS          2014-12-16 02:26:00.000000000  2014-12-16 02:28:00.000000000  1                  CSH             1.090000033378601     -73.98672485351562  40.75642013549805   1.0          nan                   -73.9964599609375    40.74289321899414   5.0                 0.5          0.5        0.0                0.0             6.0                 32.70000100135803   2.0                  4.587155818939209   2          1                 11          0"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:17:43.038261Z",
     "start_time": "2019-07-13T14:17:42.972376Z"
    }
   },
   "outputs": [],
   "source": [
    "import vaex.ml"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:18:00.833732Z",
     "start_time": "2019-07-13T14:18:00.828508Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "223.27361155622523"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# arc-distance in miles\n",
    "def arc_distance(theta_1, phi_1, theta_2, phi_2):\n",
    "    temp = (np.sin((theta_2-theta_1)/2*np.pi/180)**2\n",
    "           + np.cos(theta_1*np.pi/180)*np.cos(theta_2*np.pi/180) * np.sin((phi_2-phi_1)/2*np.pi/180)**2)\n",
    "    distance = 2 * np.arctan2(np.sqrt(temp), np.sqrt(1-temp))\n",
    "    return distance * 3958.8\n",
    "\n",
    "# distance London - Utrecht [miles]\n",
    "arc_distance(51.5069797, -0.1295992, 52.0842715, 5.0124523)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:18:14.836107Z",
     "start_time": "2019-07-13T14:18:14.830712Z"
    }
   },
   "outputs": [],
   "source": [
    "# Add the arc-distance in miles as a virtual column\n",
    "df_train['arc_distance_miles_numpy'] = arc_distance(df_train.pickup_longitude, df_train.pickup_latitude, \n",
    "                                              df_train.dropoff_longitude, df_train.dropoff_latitude)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:18:39.195747Z",
     "start_time": "2019-07-13T14:18:19.476682Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################]:  100.00% elapsed time  :       19s =  0.3m =  0.0h            \n",
      " "
     ]
    },
    {
     "data": {
      "text/plain": [
       "array(8.324456e+08, dtype=float32)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train['arc_distance_miles_numpy'].sum(progress=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:18:39.464358Z",
     "start_time": "2019-07-13T14:18:39.197045Z"
    }
   },
   "outputs": [],
   "source": [
    "df_train['arc_distance_miles_cuda'] = df_train['arc_distance_miles_numpy'].jit_cuda()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:18:47.543092Z",
     "start_time": "2019-07-13T14:18:41.786352Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################]:  100.00% elapsed time  :        5s =  0.1m =  0.0h          \n",
      " "
     ]
    },
    {
     "data": {
      "text/plain": [
       "array(8.27308e+08, dtype=float32)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train['arc_distance_miles_cuda'].sum(progress=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:18:50.192417Z",
     "start_time": "2019-07-13T14:18:50.190277Z"
    }
   },
   "outputs": [],
   "source": [
    "# choose GPU or CPU\n",
    "df_train['arc_distance_miles'] = df_train['arc_distance_miles_cuda']\n",
    "# df_train['arc_distance_miles'] = df_train['arc_distance_miles_numpy']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:18:56.624293Z",
     "start_time": "2019-07-13T14:18:56.503594Z"
    }
   },
   "outputs": [],
   "source": [
    "# direction of travel in degrees\n",
    "def direction_angle(theta_1, phi_1, theta_2, phi_2):\n",
    "    dtheta = theta_2 - theta_1\n",
    "    dphi = phi_2 - phi_1\n",
    "    radians = np.arctan2(dtheta, dphi)\n",
    "    return np.rad2deg(radians)\n",
    "\n",
    "# The direction of travel\n",
    "df_train['direction_angle'] = direction_angle(df_train.pickup_longitude, df_train.pickup_latitude, \n",
    "                                           df_train.dropoff_longitude, df_train.dropoff_latitude).jit_numba()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:19:07.421487Z",
     "start_time": "2019-07-13T14:19:07.131045Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th>#                            </th><th>vendor_id  </th><th>pickup_datetime              </th><th>dropoff_datetime             </th><th style=\"text-align: right;\">  passenger_count</th><th>payment_type  </th><th style=\"text-align: right;\">  trip_distance</th><th style=\"text-align: right;\">  pickup_longitude</th><th style=\"text-align: right;\">  pickup_latitude</th><th style=\"text-align: right;\">  rate_code</th><th style=\"text-align: right;\">  store_and_fwd_flag</th><th style=\"text-align: right;\">  dropoff_longitude</th><th style=\"text-align: right;\">  dropoff_latitude</th><th style=\"text-align: right;\">  fare_amount</th><th style=\"text-align: right;\">  surcharge</th><th style=\"text-align: right;\">  mta_tax</th><th style=\"text-align: right;\">  tip_amount</th><th style=\"text-align: right;\">  tolls_amount</th><th style=\"text-align: right;\">  total_amount</th><th style=\"text-align: right;\">  trip_speed_mph</th><th style=\"text-align: right;\">  trip_duration_min</th><th style=\"text-align: right;\">  fare_by_distance</th><th style=\"text-align: right;\">  pu_hour</th><th style=\"text-align: right;\">  pu_day_of_week</th><th style=\"text-align: right;\">  pu_month</th><th style=\"text-align: right;\">  pu_is_weekend</th><th style=\"text-align: right;\">  arc_distance_miles_numpy</th><th style=\"text-align: right;\">  arc_distance_miles_cuda</th><th style=\"text-align: right;\">  arc_distance_miles</th><th style=\"text-align: right;\">  direction_angle</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td><i style='opacity: 0.6'>0</i></td><td>VTS        </td><td>2009-01-04 02:52:00.000000000</td><td>2009-01-04 03:02:00.000000000</td><td style=\"text-align: right;\">                1</td><td>CASH          </td><td style=\"text-align: right;\">           2.63</td><td style=\"text-align: right;\">          -73.992 </td><td style=\"text-align: right;\">          40.7216</td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.9938</td><td style=\"text-align: right;\">           40.6959</td><td style=\"text-align: right;\">          8.9</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        0   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">          9.4 </td><td style=\"text-align: right;\">        15.78   </td><td style=\"text-align: right;\">           10      </td><td style=\"text-align: right;\">           3.38403</td><td style=\"text-align: right;\">        2</td><td style=\"text-align: right;\">               6</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">                  0.504949</td><td style=\"text-align: right;\">                 0.504949</td><td style=\"text-align: right;\">            0.504949</td><td style=\"text-align: right;\">        -175.882 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1</i></td><td>VTS        </td><td>2009-01-04 03:31:00.000000000</td><td>2009-01-04 03:38:00.000000000</td><td style=\"text-align: right;\">                3</td><td>Credit        </td><td style=\"text-align: right;\">           4.55</td><td style=\"text-align: right;\">          -73.9821</td><td style=\"text-align: right;\">          40.7363</td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.9558</td><td style=\"text-align: right;\">           40.768 </td><td style=\"text-align: right;\">         12.1</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        2   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">         14.6 </td><td style=\"text-align: right;\">        39      </td><td style=\"text-align: right;\">            7      </td><td style=\"text-align: right;\">           2.65934</td><td style=\"text-align: right;\">        3</td><td style=\"text-align: right;\">               6</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">                  1.91233 </td><td style=\"text-align: right;\">                 1.91233 </td><td style=\"text-align: right;\">            1.91233 </td><td style=\"text-align: right;\">          39.5963</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>2</i></td><td>DDS        </td><td>2009-01-01 20:52:58.000000000</td><td>2009-01-01 21:14:00.000000000</td><td style=\"text-align: right;\">                1</td><td>CREDIT        </td><td style=\"text-align: right;\">           5   </td><td style=\"text-align: right;\">          -73.9743</td><td style=\"text-align: right;\">          40.791 </td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.9966</td><td style=\"text-align: right;\">           40.7318</td><td style=\"text-align: right;\">         14.9</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        3.05</td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">         18.45</td><td style=\"text-align: right;\">        14.2631 </td><td style=\"text-align: right;\">           21.0333 </td><td style=\"text-align: right;\">           2.98   </td><td style=\"text-align: right;\">       20</td><td style=\"text-align: right;\">               3</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              0</td><td style=\"text-align: right;\">                  1.90838 </td><td style=\"text-align: right;\">                 1.90838 </td><td style=\"text-align: right;\">            1.90838 </td><td style=\"text-align: right;\">        -159.335 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>3</i></td><td>DDS        </td><td>2009-01-24 16:18:23.000000000</td><td>2009-01-24 16:24:56.000000000</td><td style=\"text-align: right;\">                1</td><td>CASH          </td><td style=\"text-align: right;\">           0.4 </td><td style=\"text-align: right;\">          -74.0016</td><td style=\"text-align: right;\">          40.7194</td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -74.0084</td><td style=\"text-align: right;\">           40.7203</td><td style=\"text-align: right;\">          3.7</td><td style=\"text-align: right;\">        0  </td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        0   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">          3.7 </td><td style=\"text-align: right;\">         3.66412</td><td style=\"text-align: right;\">            6.55   </td><td style=\"text-align: right;\">           9.25   </td><td style=\"text-align: right;\">       16</td><td style=\"text-align: right;\">               5</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">                  0.470047</td><td style=\"text-align: right;\">                 0.470047</td><td style=\"text-align: right;\">            0.470047</td><td style=\"text-align: right;\">         -81.9194</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>4</i></td><td>DDS        </td><td>2009-01-16 22:35:59.000000000</td><td>2009-01-16 22:43:35.000000000</td><td style=\"text-align: right;\">                2</td><td>CASH          </td><td style=\"text-align: right;\">           1.2 </td><td style=\"text-align: right;\">          -73.9898</td><td style=\"text-align: right;\">          40.735 </td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.985 </td><td style=\"text-align: right;\">           40.7245</td><td style=\"text-align: right;\">          6.1</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        0   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">          6.6 </td><td style=\"text-align: right;\">         9.47368</td><td style=\"text-align: right;\">            7.6    </td><td style=\"text-align: right;\">           5.08333</td><td style=\"text-align: right;\">       22</td><td style=\"text-align: right;\">               4</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              0</td><td style=\"text-align: right;\">                  0.386479</td><td style=\"text-align: right;\">                 0.386479</td><td style=\"text-align: right;\">            0.386479</td><td style=\"text-align: right;\">         155.526 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>5</i></td><td>DDS        </td><td>2009-01-21 08:55:57.000000000</td><td>2009-01-21 09:05:42.000000000</td><td style=\"text-align: right;\">                1</td><td>CREDIT        </td><td style=\"text-align: right;\">           0.4 </td><td style=\"text-align: right;\">          -73.984 </td><td style=\"text-align: right;\">          40.7435</td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.9803</td><td style=\"text-align: right;\">           40.7489</td><td style=\"text-align: right;\">          5.7</td><td style=\"text-align: right;\">        0  </td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        1   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">          6.7 </td><td style=\"text-align: right;\">         2.46154</td><td style=\"text-align: right;\">            9.75   </td><td style=\"text-align: right;\">          14.25   </td><td style=\"text-align: right;\">        8</td><td style=\"text-align: right;\">               2</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              0</td><td style=\"text-align: right;\">                  0.280856</td><td style=\"text-align: right;\">                 0.280856</td><td style=\"text-align: right;\">            0.280856</td><td style=\"text-align: right;\">          35.1282</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>6</i></td><td>VTS        </td><td>2009-01-04 04:31:00.000000000</td><td>2009-01-04 04:36:00.000000000</td><td style=\"text-align: right;\">                1</td><td>CASH          </td><td style=\"text-align: right;\">           1.72</td><td style=\"text-align: right;\">          -73.9926</td><td style=\"text-align: right;\">          40.7484</td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.9956</td><td style=\"text-align: right;\">           40.7283</td><td style=\"text-align: right;\">          6.1</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        0   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">          6.6 </td><td style=\"text-align: right;\">        20.64   </td><td style=\"text-align: right;\">            5      </td><td style=\"text-align: right;\">           3.54651</td><td style=\"text-align: right;\">        4</td><td style=\"text-align: right;\">               6</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">                  0.432931</td><td style=\"text-align: right;\">                 0.432931</td><td style=\"text-align: right;\">            0.432931</td><td style=\"text-align: right;\">        -171.647 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>7</i></td><td>CMT        </td><td>2009-01-05 16:29:02.000000000</td><td>2009-01-05 16:40:21.000000000</td><td style=\"text-align: right;\">                1</td><td>Credit        </td><td style=\"text-align: right;\">           1.6 </td><td style=\"text-align: right;\">          -73.9697</td><td style=\"text-align: right;\">          40.7492</td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.9904</td><td style=\"text-align: right;\">           40.7511</td><td style=\"text-align: right;\">          8.7</td><td style=\"text-align: right;\">        0  </td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        1.3 </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">         10   </td><td style=\"text-align: right;\">         8.48306</td><td style=\"text-align: right;\">           11.3167 </td><td style=\"text-align: right;\">           5.4375 </td><td style=\"text-align: right;\">       16</td><td style=\"text-align: right;\">               0</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              0</td><td style=\"text-align: right;\">                  1.43216 </td><td style=\"text-align: right;\">                 1.43216 </td><td style=\"text-align: right;\">            1.43216 </td><td style=\"text-align: right;\">         -84.9292</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>8</i></td><td>CMT        </td><td>2009-01-05 18:53:13.000000000</td><td>2009-01-05 18:57:45.000000000</td><td style=\"text-align: right;\">                1</td><td>Cash          </td><td style=\"text-align: right;\">           0.7 </td><td style=\"text-align: right;\">          -73.9552</td><td style=\"text-align: right;\">          40.783 </td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.9586</td><td style=\"text-align: right;\">           40.7748</td><td style=\"text-align: right;\">          5.9</td><td style=\"text-align: right;\">        0  </td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        0   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">          5.9 </td><td style=\"text-align: right;\">         9.26471</td><td style=\"text-align: right;\">            4.53333</td><td style=\"text-align: right;\">           8.42857</td><td style=\"text-align: right;\">       18</td><td style=\"text-align: right;\">               0</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              0</td><td style=\"text-align: right;\">                  0.28401 </td><td style=\"text-align: right;\">                 0.28401 </td><td style=\"text-align: right;\">            0.28401 </td><td style=\"text-align: right;\">        -157.378 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>9</i></td><td>CMT        </td><td>2009-01-05 08:15:38.000000000</td><td>2009-01-05 08:16:44.000000000</td><td style=\"text-align: right;\">                1</td><td>Cash          </td><td style=\"text-align: right;\">           0.3 </td><td style=\"text-align: right;\">          -73.9868</td><td style=\"text-align: right;\">          40.7509</td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.9841</td><td style=\"text-align: right;\">           40.7514</td><td style=\"text-align: right;\">          2.9</td><td style=\"text-align: right;\">        0  </td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        0   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">          2.9 </td><td style=\"text-align: right;\">        16.3636 </td><td style=\"text-align: right;\">            1.1    </td><td style=\"text-align: right;\">           9.66667</td><td style=\"text-align: right;\">        8</td><td style=\"text-align: right;\">               0</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              0</td><td style=\"text-align: right;\">                  0.187426</td><td style=\"text-align: right;\">                 0.187426</td><td style=\"text-align: right;\">            0.187426</td><td style=\"text-align: right;\">          78.6125</td></tr>\n",
       "</tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "  #  vendor_id    pickup_datetime                dropoff_datetime                 passenger_count  payment_type      trip_distance    pickup_longitude    pickup_latitude    rate_code    store_and_fwd_flag    dropoff_longitude    dropoff_latitude    fare_amount    surcharge    mta_tax    tip_amount    tolls_amount    total_amount    trip_speed_mph    trip_duration_min    fare_by_distance    pu_hour    pu_day_of_week    pu_month    pu_is_weekend    arc_distance_miles_numpy    arc_distance_miles_cuda    arc_distance_miles    direction_angle\n",
       "  0  VTS          2009-01-04 02:52:00.000000000  2009-01-04 03:02:00.000000000                  1  CASH                       2.63            -73.992             40.7216          nan                   nan             -73.9938             40.6959            8.9          0.5        nan          0                  0            9.4           15.78                10                   3.38403          2                 6           0                1                    0.504949                   0.504949              0.504949          -175.882\n",
       "  1  VTS          2009-01-04 03:31:00.000000000  2009-01-04 03:38:00.000000000                  3  Credit                     4.55            -73.9821            40.7363          nan                   nan             -73.9558             40.768            12.1          0.5        nan          2                  0           14.6           39                    7                   2.65934          3                 6           0                1                    1.91233                    1.91233               1.91233             39.5963\n",
       "  2  DDS          2009-01-01 20:52:58.000000000  2009-01-01 21:14:00.000000000                  1  CREDIT                     5               -73.9743            40.791           nan                   nan             -73.9966             40.7318           14.9          0.5        nan          3.05               0           18.45          14.2631              21.0333              2.98            20                 3           0                0                    1.90838                    1.90838               1.90838           -159.335\n",
       "  3  DDS          2009-01-24 16:18:23.000000000  2009-01-24 16:24:56.000000000                  1  CASH                       0.4             -74.0016            40.7194          nan                   nan             -74.0084             40.7203            3.7          0          nan          0                  0            3.7            3.66412              6.55                9.25            16                 5           0                1                    0.470047                   0.470047              0.470047           -81.9194\n",
       "  4  DDS          2009-01-16 22:35:59.000000000  2009-01-16 22:43:35.000000000                  2  CASH                       1.2             -73.9898            40.735           nan                   nan             -73.985              40.7245            6.1          0.5        nan          0                  0            6.6            9.47368              7.6                 5.08333         22                 4           0                0                    0.386479                   0.386479              0.386479           155.526\n",
       "  5  DDS          2009-01-21 08:55:57.000000000  2009-01-21 09:05:42.000000000                  1  CREDIT                     0.4             -73.984             40.7435          nan                   nan             -73.9803             40.7489            5.7          0          nan          1                  0            6.7            2.46154              9.75               14.25             8                 2           0                0                    0.280856                   0.280856              0.280856            35.1282\n",
       "  6  VTS          2009-01-04 04:31:00.000000000  2009-01-04 04:36:00.000000000                  1  CASH                       1.72            -73.9926            40.7484          nan                   nan             -73.9956             40.7283            6.1          0.5        nan          0                  0            6.6           20.64                 5                   3.54651          4                 6           0                1                    0.432931                   0.432931              0.432931          -171.647\n",
       "  7  CMT          2009-01-05 16:29:02.000000000  2009-01-05 16:40:21.000000000                  1  Credit                     1.6             -73.9697            40.7492          nan                   nan             -73.9904             40.7511            8.7          0          nan          1.3                0           10              8.48306             11.3167              5.4375          16                 0           0                0                    1.43216                    1.43216               1.43216            -84.9292\n",
       "  8  CMT          2009-01-05 18:53:13.000000000  2009-01-05 18:57:45.000000000                  1  Cash                       0.7             -73.9552            40.783           nan                   nan             -73.9586             40.7748            5.9          0          nan          0                  0            5.9            9.26471              4.53333             8.42857         18                 0           0                0                    0.28401                    0.28401               0.28401           -157.378\n",
       "  9  CMT          2009-01-05 08:15:38.000000000  2009-01-05 08:16:44.000000000                  1  Cash                       0.3             -73.9868            40.7509          nan                   nan             -73.9841             40.7514            2.9          0          nan          0                  0            2.9           16.3636               1.1                 9.66667          8                 0           0                0                    0.187426                   0.187426              0.187426            78.6125"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Examine the train DataFrame at this point \n",
    "df_train.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Encoding and transforming of features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:19:43.827570Z",
     "start_time": "2019-07-13T14:19:26.516581Z"
    }
   },
   "outputs": [],
   "source": [
    "# PCA of the pickup and dropoff locations - helps to \"straighten out\" the coordinates\n",
    "\n",
    "# pickup transformations\n",
    "pca_pu = vaex.ml.PCA(features=['pickup_longitude', 'pickup_latitude'], n_components=2)\n",
    "df_train = pca_pu.fit_transform(df_train)\n",
    "\n",
    "# dropoff transformations\n",
    "pca_do = vaex.ml.PCA(features=['dropoff_longitude', 'dropoff_latitude'], n_components=2)\n",
    "df_train = pca_do.fit_transform(df_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:20:09.364197Z",
     "start_time": "2019-07-13T14:19:43.828922Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14, 5))\n",
    "\n",
    "plt.subplot(121)\n",
    "plt.title('pickup - original')\n",
    "df_train.plot(df_train.pickup_longitude, df_train.pickup_latitude,\n",
    "           colormap='plasma', f='log1p', shape=256, colorbar=False)\n",
    "\n",
    "plt.subplot(122)\n",
    "plt.title('pickup - PCA transformed')\n",
    "df_train.plot(df_train.PCA_0, df_train.PCA_1,\n",
    "           colormap='plasma', f='log1p', shape=256, colorbar=False)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:20:34.682539Z",
     "start_time": "2019-07-13T14:20:24.293632Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################]:  100.00% elapsed time  :       10s =  0.2m =  0.0h\n",
      " "
     ]
    },
    {
     "data": {
      "text/plain": [
       "csh          357958192\n",
       "crd          346001379\n",
       "cash         118143531\n",
       "cas           53341764\n",
       "credit        40950658\n",
       "cre           28254498\n",
       "unk             960561\n",
       "noc             793616\n",
       "no charge       365536\n",
       "dis             285498\n",
       "no              141147\n",
       "dispute          65914\n",
       "na               28525\n",
       "dtype: int64"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Inspect the payment_type\n",
    "df_train.payment_type.str.lower().value_counts(progress=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Inspect the _payment_\\__type_\n",
    "From the documentation provided:\n",
    "- 1 = Credit card\n",
    "- 2 = Cash\n",
    "- 3 = No charge\n",
    "- 4 = Dispute\n",
    "- 5 = Unknown\n",
    "- 6 = Voided trip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:20:58.273675Z",
     "start_time": "2019-07-13T14:20:49.463902Z"
    }
   },
   "outputs": [],
   "source": [
    "# Define a mapping dictionary\n",
    "map_payment_type = {'csh': 2, 'crd': 1, 'cash': 2, '1': 1, 'cas': 2, '2': 2, 'credit': 1, 'cre': 1, 'unk': 5, \n",
    "                    'noc': 3, 'no charge': 3, '3':3, 'dis': 4, 'no ': 3, '4': 4, 'dispute': 4, 'na ': 5, '5':5}\n",
    "\n",
    "df_train['payment_type_'] = df_train.payment_type.str.lower().map(map_payment_type, \n",
    "                                                                  default_value=-1, \n",
    "                                                                  allow_missing=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:21:15.605409Z",
     "start_time": "2019-07-13T14:21:15.332088Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th>#                            </th><th>vendor_id  </th><th>pickup_datetime              </th><th>dropoff_datetime             </th><th style=\"text-align: right;\">  passenger_count</th><th>payment_type  </th><th style=\"text-align: right;\">  trip_distance</th><th style=\"text-align: right;\">  pickup_longitude</th><th style=\"text-align: right;\">  pickup_latitude</th><th style=\"text-align: right;\">  rate_code</th><th style=\"text-align: right;\">  store_and_fwd_flag</th><th style=\"text-align: right;\">  dropoff_longitude</th><th style=\"text-align: right;\">  dropoff_latitude</th><th style=\"text-align: right;\">  fare_amount</th><th style=\"text-align: right;\">  surcharge</th><th style=\"text-align: right;\">  mta_tax</th><th style=\"text-align: right;\">  tip_amount</th><th style=\"text-align: right;\">  tolls_amount</th><th style=\"text-align: right;\">  total_amount</th><th style=\"text-align: right;\">  trip_speed_mph</th><th style=\"text-align: right;\">  trip_duration_min</th><th style=\"text-align: right;\">  fare_by_distance</th><th style=\"text-align: right;\">  pu_hour</th><th style=\"text-align: right;\">  pu_day_of_week</th><th style=\"text-align: right;\">  pu_month</th><th style=\"text-align: right;\">  pu_is_weekend</th><th style=\"text-align: right;\">  arc_distance_miles_numpy</th><th style=\"text-align: right;\">  arc_distance_miles_cuda</th><th style=\"text-align: right;\">  arc_distance_miles</th><th style=\"text-align: right;\">  direction_angle</th><th style=\"text-align: right;\">     PCA_0</th><th style=\"text-align: right;\">      PCA_1</th><th style=\"text-align: right;\">     PCA_2</th><th style=\"text-align: right;\">      PCA_3</th><th style=\"text-align: right;\">  payment_type_</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td><i style='opacity: 0.6'>0</i></td><td>VTS        </td><td>2009-01-04 02:52:00.000000000</td><td>2009-01-04 03:02:00.000000000</td><td style=\"text-align: right;\">                1</td><td>CASH          </td><td style=\"text-align: right;\">           2.63</td><td style=\"text-align: right;\">          -73.992 </td><td style=\"text-align: right;\">          40.7216</td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.9938</td><td style=\"text-align: right;\">           40.6959</td><td style=\"text-align: right;\">          8.9</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        0   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">          9.4 </td><td style=\"text-align: right;\">        15.78   </td><td style=\"text-align: right;\">            10     </td><td style=\"text-align: right;\">           3.38403</td><td style=\"text-align: right;\">        2</td><td style=\"text-align: right;\">               6</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">                  0.504949</td><td style=\"text-align: right;\">                 0.504949</td><td style=\"text-align: right;\">            0.504949</td><td style=\"text-align: right;\">        -175.882 </td><td style=\"text-align: right;\"> 0.0307305</td><td style=\"text-align: right;\"> 0.0126052 </td><td style=\"text-align: right;\">-0.0546334</td><td style=\"text-align: right;\">-0.0217226 </td><td style=\"text-align: right;\">              2</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1</i></td><td>VTS        </td><td>2009-01-04 03:31:00.000000000</td><td>2009-01-04 03:38:00.000000000</td><td style=\"text-align: right;\">                3</td><td>Credit        </td><td style=\"text-align: right;\">           4.55</td><td style=\"text-align: right;\">          -73.9821</td><td style=\"text-align: right;\">          40.7363</td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.9558</td><td style=\"text-align: right;\">           40.768 </td><td style=\"text-align: right;\">         12.1</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        2   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">         14.6 </td><td style=\"text-align: right;\">        39      </td><td style=\"text-align: right;\">             7     </td><td style=\"text-align: right;\">           2.65934</td><td style=\"text-align: right;\">        3</td><td style=\"text-align: right;\">               6</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">                  1.91233 </td><td style=\"text-align: right;\">                 1.91233 </td><td style=\"text-align: right;\">            1.91233 </td><td style=\"text-align: right;\">          39.5963</td><td style=\"text-align: right;\"> 0.0133606</td><td style=\"text-align: right;\"> 0.00910222</td><td style=\"text-align: right;\"> 0.0255291</td><td style=\"text-align: right;\">-0.0070996 </td><td style=\"text-align: right;\">              1</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>2</i></td><td>DDS        </td><td>2009-01-01 20:52:58.000000000</td><td>2009-01-01 21:14:00.000000000</td><td style=\"text-align: right;\">                1</td><td>CREDIT        </td><td style=\"text-align: right;\">           5   </td><td style=\"text-align: right;\">          -73.9743</td><td style=\"text-align: right;\">          40.791 </td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.9966</td><td style=\"text-align: right;\">           40.7318</td><td style=\"text-align: right;\">         14.9</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        3.05</td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">         18.45</td><td style=\"text-align: right;\">        14.2631 </td><td style=\"text-align: right;\">            21.0333</td><td style=\"text-align: right;\">           2.98   </td><td style=\"text-align: right;\">       20</td><td style=\"text-align: right;\">               3</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              0</td><td style=\"text-align: right;\">                  1.90838 </td><td style=\"text-align: right;\">                 1.90838 </td><td style=\"text-align: right;\">            1.90838 </td><td style=\"text-align: right;\">        -159.335 </td><td style=\"text-align: right;\">-0.0307168</td><td style=\"text-align: right;\">-0.0241663 </td><td style=\"text-align: right;\">-0.0280609</td><td style=\"text-align: right;\"> 0.00261305</td><td style=\"text-align: right;\">              1</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>3</i></td><td>DDS        </td><td>2009-01-24 16:18:23.000000000</td><td>2009-01-24 16:24:56.000000000</td><td style=\"text-align: right;\">                1</td><td>CASH          </td><td style=\"text-align: right;\">           0.4 </td><td style=\"text-align: right;\">          -74.0016</td><td style=\"text-align: right;\">          40.7194</td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -74.0084</td><td style=\"text-align: right;\">           40.7203</td><td style=\"text-align: right;\">          3.7</td><td style=\"text-align: right;\">        0  </td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        0   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">          3.7 </td><td style=\"text-align: right;\">         3.66412</td><td style=\"text-align: right;\">             6.55  </td><td style=\"text-align: right;\">           9.25   </td><td style=\"text-align: right;\">       16</td><td style=\"text-align: right;\">               5</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">                  0.470047</td><td style=\"text-align: right;\">                 0.470047</td><td style=\"text-align: right;\">            0.470047</td><td style=\"text-align: right;\">         -81.9194</td><td style=\"text-align: right;\"> 0.0390947</td><td style=\"text-align: right;\"> 0.00737469</td><td style=\"text-align: right;\">-0.0444038</td><td style=\"text-align: right;\"> 0.00481617</td><td style=\"text-align: right;\">              2</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>4</i></td><td>DDS        </td><td>2009-01-16 22:35:59.000000000</td><td>2009-01-16 22:43:35.000000000</td><td style=\"text-align: right;\">                2</td><td>CASH          </td><td style=\"text-align: right;\">           1.2 </td><td style=\"text-align: right;\">          -73.9898</td><td style=\"text-align: right;\">          40.735 </td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.985 </td><td style=\"text-align: right;\">           40.7245</td><td style=\"text-align: right;\">          6.1</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        0   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">          6.6 </td><td style=\"text-align: right;\">         9.47368</td><td style=\"text-align: right;\">             7.6   </td><td style=\"text-align: right;\">           5.08333</td><td style=\"text-align: right;\">       22</td><td style=\"text-align: right;\">               4</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              0</td><td style=\"text-align: right;\">                  0.386479</td><td style=\"text-align: right;\">                 0.386479</td><td style=\"text-align: right;\">            0.386479</td><td style=\"text-align: right;\">         155.526 </td><td style=\"text-align: right;\"> 0.0197343</td><td style=\"text-align: right;\"> 0.00458489</td><td style=\"text-align: right;\">-0.0267306</td><td style=\"text-align: right;\">-0.0110029 </td><td style=\"text-align: right;\">              2</td></tr>\n",
       "</tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "  #  vendor_id    pickup_datetime                dropoff_datetime                 passenger_count  payment_type      trip_distance    pickup_longitude    pickup_latitude    rate_code    store_and_fwd_flag    dropoff_longitude    dropoff_latitude    fare_amount    surcharge    mta_tax    tip_amount    tolls_amount    total_amount    trip_speed_mph    trip_duration_min    fare_by_distance    pu_hour    pu_day_of_week    pu_month    pu_is_weekend    arc_distance_miles_numpy    arc_distance_miles_cuda    arc_distance_miles    direction_angle       PCA_0        PCA_1       PCA_2        PCA_3    payment_type_\n",
       "  0  VTS          2009-01-04 02:52:00.000000000  2009-01-04 03:02:00.000000000                  1  CASH                       2.63            -73.992             40.7216          nan                   nan             -73.9938             40.6959            8.9          0.5        nan          0                  0            9.4           15.78                 10                  3.38403          2                 6           0                1                    0.504949                   0.504949              0.504949          -175.882    0.0307305   0.0126052   -0.0546334  -0.0217226                 2\n",
       "  1  VTS          2009-01-04 03:31:00.000000000  2009-01-04 03:38:00.000000000                  3  Credit                     4.55            -73.9821            40.7363          nan                   nan             -73.9558             40.768            12.1          0.5        nan          2                  0           14.6           39                     7                  2.65934          3                 6           0                1                    1.91233                    1.91233               1.91233             39.5963   0.0133606   0.00910222   0.0255291  -0.0070996                 1\n",
       "  2  DDS          2009-01-01 20:52:58.000000000  2009-01-01 21:14:00.000000000                  1  CREDIT                     5               -73.9743            40.791           nan                   nan             -73.9966             40.7318           14.9          0.5        nan          3.05               0           18.45          14.2631               21.0333             2.98            20                 3           0                0                    1.90838                    1.90838               1.90838           -159.335   -0.0307168  -0.0241663   -0.0280609   0.00261305                1\n",
       "  3  DDS          2009-01-24 16:18:23.000000000  2009-01-24 16:24:56.000000000                  1  CASH                       0.4             -74.0016            40.7194          nan                   nan             -74.0084             40.7203            3.7          0          nan          0                  0            3.7            3.66412               6.55               9.25            16                 5           0                1                    0.470047                   0.470047              0.470047           -81.9194   0.0390947   0.00737469  -0.0444038   0.00481617                2\n",
       "  4  DDS          2009-01-16 22:35:59.000000000  2009-01-16 22:43:35.000000000                  2  CASH                       1.2             -73.9898            40.735           nan                   nan             -73.985              40.7245            6.1          0.5        nan          0                  0            6.6            9.47368               7.6                5.08333         22                 4           0                0                    0.386479                   0.386479              0.386479           155.526    0.0197343   0.00458489  -0.0267306  -0.0110029                 2"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# inspect the DataFrame\n",
    "df_train.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Setting up the predictor - `LightGBM`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:21:18.988554Z",
     "start_time": "2019-07-13T14:21:18.985888Z"
    }
   },
   "outputs": [],
   "source": [
    "features_lgbm = ['passenger_count', 'trip_distance', 'rate_code', 'pu_hour', 'pu_day_of_week', 'pu_is_weekend', \n",
    "                 'arc_distance_miles', 'direction_angle', 'PCA_0', 'PCA_1', 'PCA_2', 'PCA_3', 'payment_type_']\n",
    "\n",
    "\n",
    "# the target\n",
    "target = 'trip_duration_min'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:21:26.977499Z",
     "start_time": "2019-07-13T14:21:26.903149Z"
    }
   },
   "outputs": [],
   "source": [
    "# Import the modeling library\n",
    "import vaex.ml.lightgbm # vaex.ml also supports XGBoost, CatBoost, scikit-learn, annoy, more to come)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:21:33.223644Z",
     "start_time": "2019-07-13T14:21:30.405498Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training completed!\n"
     ]
    }
   ],
   "source": [
    "# parameters - standard lightgbm options\n",
    "params = {\n",
    "    'learning_rate': 0.1,       \n",
    "    'max_depth': 5,             \n",
    "    'colsample_bytree': 0.8,\n",
    "    'subsample': 0.8,           \n",
    "    'reg_lambda': 1,            \n",
    "    'reg_alpha': 0,             \n",
    "    'min_child_weight': 1,      \n",
    "    'objective': 'regression',  \n",
    "    'random_state': 42,         \n",
    "    'n_jobs': -1} \n",
    "\n",
    "# Instantiate the model object\n",
    "booster = vaex.ml.lightgbm.LightGBMModel(features=features_lgbm, params=params, num_boost_round=100)\n",
    "\n",
    "# Take small part of the training set to we can do the training in real time fast\n",
    "df_train_mini = df_train[:1_000_000]\n",
    "\n",
    "# Fit the model object\n",
    "booster.fit(df_train_mini, target=target)\n",
    "\n",
    "print('Training completed!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:21:40.661564Z",
     "start_time": "2019-07-13T14:21:39.343064Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([10.31321343, 11.55018209, 19.73383297, ...,  9.10644488,\n",
       "        6.42894891, 14.51054095])"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th>#                            </th><th>vendor_id  </th><th>pickup_datetime              </th><th>dropoff_datetime             </th><th style=\"text-align: right;\">  passenger_count</th><th>payment_type  </th><th style=\"text-align: right;\">  trip_distance</th><th style=\"text-align: right;\">  pickup_longitude</th><th style=\"text-align: right;\">  pickup_latitude</th><th style=\"text-align: right;\">  rate_code</th><th style=\"text-align: right;\">  store_and_fwd_flag</th><th style=\"text-align: right;\">  dropoff_longitude</th><th style=\"text-align: right;\">  dropoff_latitude</th><th style=\"text-align: right;\">  fare_amount</th><th style=\"text-align: right;\">  surcharge</th><th style=\"text-align: right;\">  mta_tax</th><th style=\"text-align: right;\">  tip_amount</th><th style=\"text-align: right;\">  tolls_amount</th><th style=\"text-align: right;\">  total_amount</th><th style=\"text-align: right;\">  trip_speed_mph</th><th style=\"text-align: right;\">  trip_duration_min</th><th style=\"text-align: right;\">  fare_by_distance</th><th style=\"text-align: right;\">  pu_hour</th><th style=\"text-align: right;\">  pu_day_of_week</th><th style=\"text-align: right;\">  pu_month</th><th style=\"text-align: right;\">  pu_is_weekend</th><th style=\"text-align: right;\">  arc_distance_miles_numpy</th><th style=\"text-align: right;\">  arc_distance_miles_cuda</th><th style=\"text-align: right;\">  arc_distance_miles</th><th style=\"text-align: right;\">  direction_angle</th><th style=\"text-align: right;\">     PCA_0</th><th style=\"text-align: right;\">      PCA_1</th><th style=\"text-align: right;\">     PCA_2</th><th style=\"text-align: right;\">      PCA_3</th><th style=\"text-align: right;\">  payment_type_</th><th style=\"text-align: right;\">  lightgbm_prediction</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td><i style='opacity: 0.6'>0</i></td><td>VTS        </td><td>2009-01-04 02:52:00.000000000</td><td>2009-01-04 03:02:00.000000000</td><td style=\"text-align: right;\">                1</td><td>CASH          </td><td style=\"text-align: right;\">           2.63</td><td style=\"text-align: right;\">          -73.992 </td><td style=\"text-align: right;\">          40.7216</td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.9938</td><td style=\"text-align: right;\">           40.6959</td><td style=\"text-align: right;\">          8.9</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        0   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">          9.4 </td><td style=\"text-align: right;\">        15.78   </td><td style=\"text-align: right;\">            10     </td><td style=\"text-align: right;\">           3.38403</td><td style=\"text-align: right;\">        2</td><td style=\"text-align: right;\">               6</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">                  0.504949</td><td style=\"text-align: right;\">                 0.504949</td><td style=\"text-align: right;\">            0.504949</td><td style=\"text-align: right;\">        -175.882 </td><td style=\"text-align: right;\"> 0.0307305</td><td style=\"text-align: right;\"> 0.0126052 </td><td style=\"text-align: right;\">-0.0546334</td><td style=\"text-align: right;\">-0.0217226 </td><td style=\"text-align: right;\">              2</td><td style=\"text-align: right;\">             10.3132 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1</i></td><td>VTS        </td><td>2009-01-04 03:31:00.000000000</td><td>2009-01-04 03:38:00.000000000</td><td style=\"text-align: right;\">                3</td><td>Credit        </td><td style=\"text-align: right;\">           4.55</td><td style=\"text-align: right;\">          -73.9821</td><td style=\"text-align: right;\">          40.7363</td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.9558</td><td style=\"text-align: right;\">           40.768 </td><td style=\"text-align: right;\">         12.1</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        2   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">         14.6 </td><td style=\"text-align: right;\">        39      </td><td style=\"text-align: right;\">             7     </td><td style=\"text-align: right;\">           2.65934</td><td style=\"text-align: right;\">        3</td><td style=\"text-align: right;\">               6</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">                  1.91233 </td><td style=\"text-align: right;\">                 1.91233 </td><td style=\"text-align: right;\">            1.91233 </td><td style=\"text-align: right;\">          39.5963</td><td style=\"text-align: right;\"> 0.0133606</td><td style=\"text-align: right;\"> 0.00910222</td><td style=\"text-align: right;\"> 0.0255291</td><td style=\"text-align: right;\">-0.0070996 </td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">             11.5502 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>2</i></td><td>DDS        </td><td>2009-01-01 20:52:58.000000000</td><td>2009-01-01 21:14:00.000000000</td><td style=\"text-align: right;\">                1</td><td>CREDIT        </td><td style=\"text-align: right;\">           5   </td><td style=\"text-align: right;\">          -73.9743</td><td style=\"text-align: right;\">          40.791 </td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.9966</td><td style=\"text-align: right;\">           40.7318</td><td style=\"text-align: right;\">         14.9</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        3.05</td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">         18.45</td><td style=\"text-align: right;\">        14.2631 </td><td style=\"text-align: right;\">            21.0333</td><td style=\"text-align: right;\">           2.98   </td><td style=\"text-align: right;\">       20</td><td style=\"text-align: right;\">               3</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              0</td><td style=\"text-align: right;\">                  1.90838 </td><td style=\"text-align: right;\">                 1.90838 </td><td style=\"text-align: right;\">            1.90838 </td><td style=\"text-align: right;\">        -159.335 </td><td style=\"text-align: right;\">-0.0307168</td><td style=\"text-align: right;\">-0.0241663 </td><td style=\"text-align: right;\">-0.0280609</td><td style=\"text-align: right;\"> 0.00261305</td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">             19.7338 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>3</i></td><td>DDS        </td><td>2009-01-24 16:18:23.000000000</td><td>2009-01-24 16:24:56.000000000</td><td style=\"text-align: right;\">                1</td><td>CASH          </td><td style=\"text-align: right;\">           0.4 </td><td style=\"text-align: right;\">          -74.0016</td><td style=\"text-align: right;\">          40.7194</td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -74.0084</td><td style=\"text-align: right;\">           40.7203</td><td style=\"text-align: right;\">          3.7</td><td style=\"text-align: right;\">        0  </td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        0   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">          3.7 </td><td style=\"text-align: right;\">         3.66412</td><td style=\"text-align: right;\">             6.55  </td><td style=\"text-align: right;\">           9.25   </td><td style=\"text-align: right;\">       16</td><td style=\"text-align: right;\">               5</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">                  0.470047</td><td style=\"text-align: right;\">                 0.470047</td><td style=\"text-align: right;\">            0.470047</td><td style=\"text-align: right;\">         -81.9194</td><td style=\"text-align: right;\"> 0.0390947</td><td style=\"text-align: right;\"> 0.00737469</td><td style=\"text-align: right;\">-0.0444038</td><td style=\"text-align: right;\"> 0.00481617</td><td style=\"text-align: right;\">              2</td><td style=\"text-align: right;\">              4.30183</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>4</i></td><td>DDS        </td><td>2009-01-16 22:35:59.000000000</td><td>2009-01-16 22:43:35.000000000</td><td style=\"text-align: right;\">                2</td><td>CASH          </td><td style=\"text-align: right;\">           1.2 </td><td style=\"text-align: right;\">          -73.9898</td><td style=\"text-align: right;\">          40.735 </td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.985 </td><td style=\"text-align: right;\">           40.7245</td><td style=\"text-align: right;\">          6.1</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        0   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">          6.6 </td><td style=\"text-align: right;\">         9.47368</td><td style=\"text-align: right;\">             7.6   </td><td style=\"text-align: right;\">           5.08333</td><td style=\"text-align: right;\">       22</td><td style=\"text-align: right;\">               4</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              0</td><td style=\"text-align: right;\">                  0.386479</td><td style=\"text-align: right;\">                 0.386479</td><td style=\"text-align: right;\">            0.386479</td><td style=\"text-align: right;\">         155.526 </td><td style=\"text-align: right;\"> 0.0197343</td><td style=\"text-align: right;\"> 0.00458489</td><td style=\"text-align: right;\">-0.0267306</td><td style=\"text-align: right;\">-0.0110029 </td><td style=\"text-align: right;\">              2</td><td style=\"text-align: right;\">              8.9789 </td></tr>\n",
       "</tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "  #  vendor_id    pickup_datetime                dropoff_datetime                 passenger_count  payment_type      trip_distance    pickup_longitude    pickup_latitude    rate_code    store_and_fwd_flag    dropoff_longitude    dropoff_latitude    fare_amount    surcharge    mta_tax    tip_amount    tolls_amount    total_amount    trip_speed_mph    trip_duration_min    fare_by_distance    pu_hour    pu_day_of_week    pu_month    pu_is_weekend    arc_distance_miles_numpy    arc_distance_miles_cuda    arc_distance_miles    direction_angle       PCA_0        PCA_1       PCA_2        PCA_3    payment_type_    lightgbm_prediction\n",
       "  0  VTS          2009-01-04 02:52:00.000000000  2009-01-04 03:02:00.000000000                  1  CASH                       2.63            -73.992             40.7216          nan                   nan             -73.9938             40.6959            8.9          0.5        nan          0                  0            9.4           15.78                 10                  3.38403          2                 6           0                1                    0.504949                   0.504949              0.504949          -175.882    0.0307305   0.0126052   -0.0546334  -0.0217226                 2               10.3132\n",
       "  1  VTS          2009-01-04 03:31:00.000000000  2009-01-04 03:38:00.000000000                  3  Credit                     4.55            -73.9821            40.7363          nan                   nan             -73.9558             40.768            12.1          0.5        nan          2                  0           14.6           39                     7                  2.65934          3                 6           0                1                    1.91233                    1.91233               1.91233             39.5963   0.0133606   0.00910222   0.0255291  -0.0070996                 1               11.5502\n",
       "  2  DDS          2009-01-01 20:52:58.000000000  2009-01-01 21:14:00.000000000                  1  CREDIT                     5               -73.9743            40.791           nan                   nan             -73.9966             40.7318           14.9          0.5        nan          3.05               0           18.45          14.2631               21.0333             2.98            20                 3           0                0                    1.90838                    1.90838               1.90838           -159.335   -0.0307168  -0.0241663   -0.0280609   0.00261305                1               19.7338\n",
       "  3  DDS          2009-01-24 16:18:23.000000000  2009-01-24 16:24:56.000000000                  1  CASH                       0.4             -74.0016            40.7194          nan                   nan             -74.0084             40.7203            3.7          0          nan          0                  0            3.7            3.66412               6.55               9.25            16                 5           0                1                    0.470047                   0.470047              0.470047           -81.9194   0.0390947   0.00737469  -0.0444038   0.00481617                2                4.30183\n",
       "  4  DDS          2009-01-16 22:35:59.000000000  2009-01-16 22:43:35.000000000                  2  CASH                       1.2             -73.9898            40.735           nan                   nan             -73.985              40.7245            6.1          0.5        nan          0                  0            6.6            9.47368               7.6                5.08333         22                 4           0                0                    0.386479                   0.386479              0.386479           155.526    0.0197343   0.00458489  -0.0267306  -0.0110029                 2                8.9789"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check performance on the training set - in reality one needs to do proper (x)-validation\n",
    "\n",
    "# Classical predict - get an in-memory array of the predictions\n",
    "pred = booster.predict(df_train_mini)\n",
    "\n",
    "# view the predictions\n",
    "display(pred)\n",
    "\n",
    "# Create a virtual column housing the predictions\n",
    "df_train = booster.transform(df_train)\n",
    "\n",
    "# view the DataFrame\n",
    "df_train.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:21:59.605497Z",
     "start_time": "2019-07-13T14:21:59.581019Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The mean absolute error is 2.317\n",
      "The mean squared score is 13.226\n"
     ]
    }
   ],
   "source": [
    "# Check the performance\n",
    "from sklearn.metrics import mean_absolute_error, mean_squared_error\n",
    "\n",
    "mae_train_score = mean_absolute_error(df_train_mini.trip_duration_min.values, pred)\n",
    "mse_train_score = mean_squared_error(df_train_mini.trip_duration_min.values, pred)\n",
    "\n",
    "print('The mean absolute error is %2.3f' % mae_train_score)\n",
    "print('The mean squared score is %2.3f' % mse_train_score)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Second estimator?!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:22:32.111403Z",
     "start_time": "2019-07-13T14:22:08.911993Z"
    }
   },
   "outputs": [],
   "source": [
    "# One hot encoding of categorical features\n",
    "one_hot_enc = vaex.ml.OneHotEncoder(features=['payment_type_', \n",
    "                                              'pu_hour', 'pu_day_of_week', 'pu_month'], prefix='onehot_')\n",
    "\n",
    "df_train = one_hot_enc.fit_transform(df_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:22:55.975656Z",
     "start_time": "2019-07-13T14:22:32.112618Z"
    }
   },
   "outputs": [],
   "source": [
    "# Standard scale some of the numerical features\n",
    "standard_scaler = vaex.ml.StandardScaler(features=['arc_distance_miles', 'direction_angle', 'trip_distance'])\n",
    "df_train = standard_scaler.fit_transform(df_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:22:56.020676Z",
     "start_time": "2019-07-13T14:22:55.976960Z"
    }
   },
   "outputs": [],
   "source": [
    "# Try a linear model\n",
    "import vaex.ml.sklearn\n",
    "from sklearn.linear_model import LinearRegression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:22:56.172651Z",
     "start_time": "2019-07-13T14:22:56.170103Z"
    }
   },
   "outputs": [],
   "source": [
    "# Specify which features to use\n",
    "features_linear = ['PCA_0', 'PCA_1', 'PCA_2', 'PCA_3', 'pu_is_weekend'] + \\\n",
    "                  [feature for feature in df_train.get_column_names() if 'standard_scaled_' in feature] + \\\n",
    "                  [feature for feature in df_train.get_column_names() if 'onehot_' in feature]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:23:03.153427Z",
     "start_time": "2019-07-13T14:22:58.439112Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training completed!\n"
     ]
    }
   ],
   "source": [
    "# Instantiate the vaex-sklearn model \n",
    "linear_model = vaex.ml.sklearn.SKLearnPredictor(model=LinearRegression(copy_X=False, n_jobs=-1), \n",
    "                                                features=features_linear, prediction_name='linear_prediction')\n",
    "\n",
    "# Agaom, take small part of the training so we can train in real time.\n",
    "df_train_mini = df_train[:1_000_000]\n",
    "\n",
    "\n",
    "# Fit the model object\n",
    "linear_model.fit(df_train_mini, target=target)\n",
    "\n",
    "print('Training completed!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:23:05.785575Z",
     "start_time": "2019-07-13T14:23:03.156262Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 9.09023565, 13.08232558, 18.55664033, ...,  9.6434135 ,\n",
       "        7.96064326, 11.91514918])"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th>#                            </th><th>vendor_id  </th><th>pickup_datetime              </th><th>dropoff_datetime             </th><th style=\"text-align: right;\">  passenger_count</th><th>payment_type  </th><th style=\"text-align: right;\">  trip_distance</th><th style=\"text-align: right;\">  pickup_longitude</th><th style=\"text-align: right;\">  pickup_latitude</th><th style=\"text-align: right;\">  rate_code</th><th style=\"text-align: right;\">  store_and_fwd_flag</th><th style=\"text-align: right;\">  dropoff_longitude</th><th style=\"text-align: right;\">  dropoff_latitude</th><th style=\"text-align: right;\">  fare_amount</th><th style=\"text-align: right;\">  surcharge</th><th style=\"text-align: right;\">  mta_tax</th><th style=\"text-align: right;\">  tip_amount</th><th style=\"text-align: right;\">  tolls_amount</th><th style=\"text-align: right;\">  total_amount</th><th style=\"text-align: right;\">  trip_speed_mph</th><th style=\"text-align: right;\">  trip_duration_min</th><th style=\"text-align: right;\">  fare_by_distance</th><th style=\"text-align: right;\">  pu_hour</th><th style=\"text-align: right;\">  pu_day_of_week</th><th style=\"text-align: right;\">  pu_month</th><th style=\"text-align: right;\">  pu_is_weekend</th><th style=\"text-align: right;\">  arc_distance_miles_numpy</th><th style=\"text-align: right;\">  arc_distance_miles_cuda</th><th style=\"text-align: right;\">  arc_distance_miles</th><th style=\"text-align: right;\">  direction_angle</th><th style=\"text-align: right;\">     PCA_0</th><th style=\"text-align: right;\">      PCA_1</th><th style=\"text-align: right;\">     PCA_2</th><th style=\"text-align: right;\">      PCA_3</th><th style=\"text-align: right;\">  payment_type_</th><th style=\"text-align: right;\">  lightgbm_prediction</th><th style=\"text-align: right;\">  onehot_payment_type__1</th><th style=\"text-align: right;\">  onehot_payment_type__2</th><th style=\"text-align: right;\">  onehot_payment_type__3</th><th style=\"text-align: right;\">  onehot_payment_type__4</th><th style=\"text-align: right;\">  onehot_payment_type__5</th><th style=\"text-align: right;\">  onehot_pu_hour_0</th><th style=\"text-align: right;\">  onehot_pu_hour_1</th><th style=\"text-align: right;\">  onehot_pu_hour_2</th><th style=\"text-align: right;\">  onehot_pu_hour_3</th><th style=\"text-align: right;\">  onehot_pu_hour_4</th><th style=\"text-align: right;\">  onehot_pu_hour_5</th><th style=\"text-align: right;\">  onehot_pu_hour_6</th><th style=\"text-align: right;\">  onehot_pu_hour_7</th><th style=\"text-align: right;\">  onehot_pu_hour_8</th><th style=\"text-align: right;\">  onehot_pu_hour_9</th><th style=\"text-align: right;\">  onehot_pu_hour_10</th><th style=\"text-align: right;\">  onehot_pu_hour_11</th><th style=\"text-align: right;\">  onehot_pu_hour_12</th><th style=\"text-align: right;\">  onehot_pu_hour_13</th><th style=\"text-align: right;\">  onehot_pu_hour_14</th><th style=\"text-align: right;\">  onehot_pu_hour_15</th><th style=\"text-align: right;\">  onehot_pu_hour_16</th><th style=\"text-align: right;\">  onehot_pu_hour_17</th><th style=\"text-align: right;\">  onehot_pu_hour_18</th><th style=\"text-align: right;\">  onehot_pu_hour_19</th><th style=\"text-align: right;\">  onehot_pu_hour_20</th><th style=\"text-align: right;\">  onehot_pu_hour_21</th><th style=\"text-align: right;\">  onehot_pu_hour_22</th><th style=\"text-align: right;\">  onehot_pu_hour_23</th><th style=\"text-align: right;\">  onehot_pu_day_of_week_0</th><th style=\"text-align: right;\">  onehot_pu_day_of_week_1</th><th style=\"text-align: right;\">  onehot_pu_day_of_week_2</th><th style=\"text-align: right;\">  onehot_pu_day_of_week_3</th><th style=\"text-align: right;\">  onehot_pu_day_of_week_4</th><th style=\"text-align: right;\">  onehot_pu_day_of_week_5</th><th style=\"text-align: right;\">  onehot_pu_day_of_week_6</th><th style=\"text-align: right;\">  onehot_pu_month_0</th><th style=\"text-align: right;\">  onehot_pu_month_1</th><th style=\"text-align: right;\">  onehot_pu_month_2</th><th style=\"text-align: right;\">  onehot_pu_month_3</th><th style=\"text-align: right;\">  onehot_pu_month_4</th><th style=\"text-align: right;\">  onehot_pu_month_5</th><th style=\"text-align: right;\">  onehot_pu_month_6</th><th style=\"text-align: right;\">  onehot_pu_month_7</th><th style=\"text-align: right;\">  onehot_pu_month_8</th><th style=\"text-align: right;\">  onehot_pu_month_9</th><th style=\"text-align: right;\">  onehot_pu_month_10</th><th style=\"text-align: right;\">  onehot_pu_month_11</th><th style=\"text-align: right;\">  standard_scaled_arc_distance_miles</th><th style=\"text-align: right;\">  standard_scaled_direction_angle</th><th style=\"text-align: right;\">  standard_scaled_trip_distance</th><th style=\"text-align: right;\">  linear_prediction</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td><i style='opacity: 0.6'>0</i></td><td>VTS        </td><td>2009-01-04 02:52:00.000000000</td><td>2009-01-04 03:02:00.000000000</td><td style=\"text-align: right;\">                1</td><td>CASH          </td><td style=\"text-align: right;\">           2.63</td><td style=\"text-align: right;\">          -73.992 </td><td style=\"text-align: right;\">          40.7216</td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.9938</td><td style=\"text-align: right;\">           40.6959</td><td style=\"text-align: right;\">          8.9</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        0   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">          9.4 </td><td style=\"text-align: right;\">        15.78   </td><td style=\"text-align: right;\">            10     </td><td style=\"text-align: right;\">           3.38403</td><td style=\"text-align: right;\">        2</td><td style=\"text-align: right;\">               6</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">                  0.504949</td><td style=\"text-align: right;\">                 0.504949</td><td style=\"text-align: right;\">            0.504949</td><td style=\"text-align: right;\">        -175.882 </td><td style=\"text-align: right;\"> 0.0307305</td><td style=\"text-align: right;\"> 0.0126052 </td><td style=\"text-align: right;\">-0.0546334</td><td style=\"text-align: right;\">-0.0217226 </td><td style=\"text-align: right;\">              2</td><td style=\"text-align: right;\">             10.3132 </td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       1</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 1</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        1</td><td style=\"text-align: right;\">                  1</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                   0</td><td style=\"text-align: right;\">                   0</td><td style=\"text-align: right;\">                           -0.614417</td><td style=\"text-align: right;\">                        -1.56023 </td><td style=\"text-align: right;\">                       0.189254</td><td style=\"text-align: right;\">            9.09024</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1</i></td><td>VTS        </td><td>2009-01-04 03:31:00.000000000</td><td>2009-01-04 03:38:00.000000000</td><td style=\"text-align: right;\">                3</td><td>Credit        </td><td style=\"text-align: right;\">           4.55</td><td style=\"text-align: right;\">          -73.9821</td><td style=\"text-align: right;\">          40.7363</td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.9558</td><td style=\"text-align: right;\">           40.768 </td><td style=\"text-align: right;\">         12.1</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        2   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">         14.6 </td><td style=\"text-align: right;\">        39      </td><td style=\"text-align: right;\">             7     </td><td style=\"text-align: right;\">           2.65934</td><td style=\"text-align: right;\">        3</td><td style=\"text-align: right;\">               6</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">                  1.91233 </td><td style=\"text-align: right;\">                 1.91233 </td><td style=\"text-align: right;\">            1.91233 </td><td style=\"text-align: right;\">          39.5963</td><td style=\"text-align: right;\"> 0.0133606</td><td style=\"text-align: right;\"> 0.00910222</td><td style=\"text-align: right;\"> 0.0255291</td><td style=\"text-align: right;\">-0.0070996 </td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">             11.5502 </td><td style=\"text-align: right;\">                       1</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 1</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        1</td><td style=\"text-align: right;\">                  1</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                   0</td><td style=\"text-align: right;\">                   0</td><td style=\"text-align: right;\">                            0.490347</td><td style=\"text-align: right;\">                         0.537361</td><td style=\"text-align: right;\">                       1.22485 </td><td style=\"text-align: right;\">           13.0823 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>2</i></td><td>DDS        </td><td>2009-01-01 20:52:58.000000000</td><td>2009-01-01 21:14:00.000000000</td><td style=\"text-align: right;\">                1</td><td>CREDIT        </td><td style=\"text-align: right;\">           5   </td><td style=\"text-align: right;\">          -73.9743</td><td style=\"text-align: right;\">          40.791 </td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.9966</td><td style=\"text-align: right;\">           40.7318</td><td style=\"text-align: right;\">         14.9</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        3.05</td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">         18.45</td><td style=\"text-align: right;\">        14.2631 </td><td style=\"text-align: right;\">            21.0333</td><td style=\"text-align: right;\">           2.98   </td><td style=\"text-align: right;\">       20</td><td style=\"text-align: right;\">               3</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              0</td><td style=\"text-align: right;\">                  1.90838 </td><td style=\"text-align: right;\">                 1.90838 </td><td style=\"text-align: right;\">            1.90838 </td><td style=\"text-align: right;\">        -159.335 </td><td style=\"text-align: right;\">-0.0307168</td><td style=\"text-align: right;\">-0.0241663 </td><td style=\"text-align: right;\">-0.0280609</td><td style=\"text-align: right;\"> 0.00261305</td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">             19.7338 </td><td style=\"text-align: right;\">                       1</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  1</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        1</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                  1</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                   0</td><td style=\"text-align: right;\">                   0</td><td style=\"text-align: right;\">                            0.487246</td><td style=\"text-align: right;\">                        -1.39915 </td><td style=\"text-align: right;\">                       1.46757 </td><td style=\"text-align: right;\">           18.5566 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>3</i></td><td>DDS        </td><td>2009-01-24 16:18:23.000000000</td><td>2009-01-24 16:24:56.000000000</td><td style=\"text-align: right;\">                1</td><td>CASH          </td><td style=\"text-align: right;\">           0.4 </td><td style=\"text-align: right;\">          -74.0016</td><td style=\"text-align: right;\">          40.7194</td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -74.0084</td><td style=\"text-align: right;\">           40.7203</td><td style=\"text-align: right;\">          3.7</td><td style=\"text-align: right;\">        0  </td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        0   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">          3.7 </td><td style=\"text-align: right;\">         3.66412</td><td style=\"text-align: right;\">             6.55  </td><td style=\"text-align: right;\">           9.25   </td><td style=\"text-align: right;\">       16</td><td style=\"text-align: right;\">               5</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">                  0.470047</td><td style=\"text-align: right;\">                 0.470047</td><td style=\"text-align: right;\">            0.470047</td><td style=\"text-align: right;\">         -81.9194</td><td style=\"text-align: right;\"> 0.0390947</td><td style=\"text-align: right;\"> 0.00737469</td><td style=\"text-align: right;\">-0.0444038</td><td style=\"text-align: right;\"> 0.00481617</td><td style=\"text-align: right;\">              2</td><td style=\"text-align: right;\">              4.30183</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       1</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  1</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        1</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                  1</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                   0</td><td style=\"text-align: right;\">                   0</td><td style=\"text-align: right;\">                           -0.641814</td><td style=\"text-align: right;\">                        -0.645546</td><td style=\"text-align: right;\">                      -1.01355 </td><td style=\"text-align: right;\">            6.25763</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>4</i></td><td>DDS        </td><td>2009-01-16 22:35:59.000000000</td><td>2009-01-16 22:43:35.000000000</td><td style=\"text-align: right;\">                2</td><td>CASH          </td><td style=\"text-align: right;\">           1.2 </td><td style=\"text-align: right;\">          -73.9898</td><td style=\"text-align: right;\">          40.735 </td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.985 </td><td style=\"text-align: right;\">           40.7245</td><td style=\"text-align: right;\">          6.1</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        0   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">          6.6 </td><td style=\"text-align: right;\">         9.47368</td><td style=\"text-align: right;\">             7.6   </td><td style=\"text-align: right;\">           5.08333</td><td style=\"text-align: right;\">       22</td><td style=\"text-align: right;\">               4</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              0</td><td style=\"text-align: right;\">                  0.386479</td><td style=\"text-align: right;\">                 0.386479</td><td style=\"text-align: right;\">            0.386479</td><td style=\"text-align: right;\">         155.526 </td><td style=\"text-align: right;\"> 0.0197343</td><td style=\"text-align: right;\"> 0.00458489</td><td style=\"text-align: right;\">-0.0267306</td><td style=\"text-align: right;\">-0.0110029 </td><td style=\"text-align: right;\">              2</td><td style=\"text-align: right;\">              8.9789 </td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       1</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  1</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        1</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                  1</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                   0</td><td style=\"text-align: right;\">                   0</td><td style=\"text-align: right;\">                           -0.707412</td><td style=\"text-align: right;\">                         1.66589 </td><td style=\"text-align: right;\">                      -0.582053</td><td style=\"text-align: right;\">            7.74905</td></tr>\n",
       "</tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "  #  vendor_id    pickup_datetime                dropoff_datetime                 passenger_count  payment_type      trip_distance    pickup_longitude    pickup_latitude    rate_code    store_and_fwd_flag    dropoff_longitude    dropoff_latitude    fare_amount    surcharge    mta_tax    tip_amount    tolls_amount    total_amount    trip_speed_mph    trip_duration_min    fare_by_distance    pu_hour    pu_day_of_week    pu_month    pu_is_weekend    arc_distance_miles_numpy    arc_distance_miles_cuda    arc_distance_miles    direction_angle       PCA_0        PCA_1       PCA_2        PCA_3    payment_type_    lightgbm_prediction    onehot_payment_type__1    onehot_payment_type__2    onehot_payment_type__3    onehot_payment_type__4    onehot_payment_type__5    onehot_pu_hour_0    onehot_pu_hour_1    onehot_pu_hour_2    onehot_pu_hour_3    onehot_pu_hour_4    onehot_pu_hour_5    onehot_pu_hour_6    onehot_pu_hour_7    onehot_pu_hour_8    onehot_pu_hour_9    onehot_pu_hour_10    onehot_pu_hour_11    onehot_pu_hour_12    onehot_pu_hour_13    onehot_pu_hour_14    onehot_pu_hour_15    onehot_pu_hour_16    onehot_pu_hour_17    onehot_pu_hour_18    onehot_pu_hour_19    onehot_pu_hour_20    onehot_pu_hour_21    onehot_pu_hour_22    onehot_pu_hour_23    onehot_pu_day_of_week_0    onehot_pu_day_of_week_1    onehot_pu_day_of_week_2    onehot_pu_day_of_week_3    onehot_pu_day_of_week_4    onehot_pu_day_of_week_5    onehot_pu_day_of_week_6    onehot_pu_month_0    onehot_pu_month_1    onehot_pu_month_2    onehot_pu_month_3    onehot_pu_month_4    onehot_pu_month_5    onehot_pu_month_6    onehot_pu_month_7    onehot_pu_month_8    onehot_pu_month_9    onehot_pu_month_10    onehot_pu_month_11    standard_scaled_arc_distance_miles    standard_scaled_direction_angle    standard_scaled_trip_distance    linear_prediction\n",
       "  0  VTS          2009-01-04 02:52:00.000000000  2009-01-04 03:02:00.000000000                  1  CASH                       2.63            -73.992             40.7216          nan                   nan             -73.9938             40.6959            8.9          0.5        nan          0                  0            9.4           15.78                 10                  3.38403          2                 6           0                1                    0.504949                   0.504949              0.504949          -175.882    0.0307305   0.0126052   -0.0546334  -0.0217226                 2               10.3132                          0                         1                         0                         0                         0                   0                   0                   1                   0                   0                   0                   0                   0                   0                   0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                          0                          0                          0                          0                          0                          0                          1                    1                    0                    0                    0                    0                    0                    0                    0                    0                    0                     0                     0                             -0.614417                          -1.56023                          0.189254              9.09024\n",
       "  1  VTS          2009-01-04 03:31:00.000000000  2009-01-04 03:38:00.000000000                  3  Credit                     4.55            -73.9821            40.7363          nan                   nan             -73.9558             40.768            12.1          0.5        nan          2                  0           14.6           39                     7                  2.65934          3                 6           0                1                    1.91233                    1.91233               1.91233             39.5963   0.0133606   0.00910222   0.0255291  -0.0070996                 1               11.5502                          1                         0                         0                         0                         0                   0                   0                   0                   1                   0                   0                   0                   0                   0                   0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                          0                          0                          0                          0                          0                          0                          1                    1                    0                    0                    0                    0                    0                    0                    0                    0                    0                     0                     0                              0.490347                           0.537361                         1.22485              13.0823\n",
       "  2  DDS          2009-01-01 20:52:58.000000000  2009-01-01 21:14:00.000000000                  1  CREDIT                     5               -73.9743            40.791           nan                   nan             -73.9966             40.7318           14.9          0.5        nan          3.05               0           18.45          14.2631               21.0333             2.98            20                 3           0                0                    1.90838                    1.90838               1.90838           -159.335   -0.0307168  -0.0241663   -0.0280609   0.00261305                1               19.7338                          1                         0                         0                         0                         0                   0                   0                   0                   0                   0                   0                   0                   0                   0                   0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    1                    0                    0                    0                          0                          0                          0                          1                          0                          0                          0                    1                    0                    0                    0                    0                    0                    0                    0                    0                    0                     0                     0                              0.487246                          -1.39915                          1.46757              18.5566\n",
       "  3  DDS          2009-01-24 16:18:23.000000000  2009-01-24 16:24:56.000000000                  1  CASH                       0.4             -74.0016            40.7194          nan                   nan             -74.0084             40.7203            3.7          0          nan          0                  0            3.7            3.66412               6.55               9.25            16                 5           0                1                    0.470047                   0.470047              0.470047           -81.9194   0.0390947   0.00737469  -0.0444038   0.00481617                2                4.30183                         0                         1                         0                         0                         0                   0                   0                   0                   0                   0                   0                   0                   0                   0                   0                    0                    0                    0                    0                    0                    0                    1                    0                    0                    0                    0                    0                    0                    0                          0                          0                          0                          0                          0                          1                          0                    1                    0                    0                    0                    0                    0                    0                    0                    0                    0                     0                     0                             -0.641814                          -0.645546                        -1.01355               6.25763\n",
       "  4  DDS          2009-01-16 22:35:59.000000000  2009-01-16 22:43:35.000000000                  2  CASH                       1.2             -73.9898            40.735           nan                   nan             -73.985              40.7245            6.1          0.5        nan          0                  0            6.6            9.47368               7.6                5.08333         22                 4           0                0                    0.386479                   0.386479              0.386479           155.526    0.0197343   0.00458489  -0.0267306  -0.0110029                 2                8.9789                          0                         1                         0                         0                         0                   0                   0                   0                   0                   0                   0                   0                   0                   0                   0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    1                    0                          0                          0                          0                          0                          1                          0                          0                    1                    0                    0                    0                    0                    0                    0                    0                    0                    0                     0                     0                             -0.707412                           1.66589                         -0.582053              7.74905"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check performance on the training set - in reality one needs to do proper (x)-validation\n",
    "\n",
    "# Classical predict - get an in-memory array of the predictions\n",
    "pred_linear = linear_model.predict(df_train_mini)\n",
    "\n",
    "# view the predictions\n",
    "display(pred_linear)\n",
    "\n",
    "# Create a virtual column housing the predictions\n",
    "df_train = linear_model.transform(df_train)\n",
    "\n",
    "# view the DataFrame \n",
    "df_train.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-12T16:03:42.152930Z",
     "start_time": "2019-07-12T16:03:42.125755Z"
    }
   },
   "outputs": [],
   "source": [
    "mae_train_score = mean_absolute_error(df_train_mini.trip_duration_min.values, pred_linear)\n",
    "mse_train_score = mean_squared_error(df_train_mini.trip_duration_min.values, pred_linear)\n",
    "\n",
    "print('The mean absolute error is %2.3f' % mae_train_score)\n",
    "print('The mean squared score is %2.3f' % mse_train_score)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ensemble?!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:23:32.562235Z",
     "start_time": "2019-07-13T14:23:32.544808Z"
    }
   },
   "outputs": [],
   "source": [
    "# Average the predictions from the Gradient Boosting and Linear models\n",
    "df_train['final_prediction'] = (df_train.lightgbm_prediction + df_train.linear_prediction) / 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:23:35.310651Z",
     "start_time": "2019-07-13T14:23:34.940872Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th>#                            </th><th>vendor_id  </th><th>pickup_datetime              </th><th>dropoff_datetime             </th><th style=\"text-align: right;\">  passenger_count</th><th>payment_type  </th><th style=\"text-align: right;\">  trip_distance</th><th style=\"text-align: right;\">  pickup_longitude</th><th style=\"text-align: right;\">  pickup_latitude</th><th style=\"text-align: right;\">  rate_code</th><th style=\"text-align: right;\">  store_and_fwd_flag</th><th style=\"text-align: right;\">  dropoff_longitude</th><th style=\"text-align: right;\">  dropoff_latitude</th><th style=\"text-align: right;\">  fare_amount</th><th style=\"text-align: right;\">  surcharge</th><th style=\"text-align: right;\">  mta_tax</th><th style=\"text-align: right;\">  tip_amount</th><th style=\"text-align: right;\">  tolls_amount</th><th style=\"text-align: right;\">  total_amount</th><th style=\"text-align: right;\">  trip_speed_mph</th><th style=\"text-align: right;\">  trip_duration_min</th><th style=\"text-align: right;\">  fare_by_distance</th><th style=\"text-align: right;\">  pu_hour</th><th style=\"text-align: right;\">  pu_day_of_week</th><th style=\"text-align: right;\">  pu_month</th><th style=\"text-align: right;\">  pu_is_weekend</th><th style=\"text-align: right;\">  arc_distance_miles_numpy</th><th style=\"text-align: right;\">  arc_distance_miles_cuda</th><th style=\"text-align: right;\">  arc_distance_miles</th><th style=\"text-align: right;\">  direction_angle</th><th style=\"text-align: right;\">     PCA_0</th><th style=\"text-align: right;\">      PCA_1</th><th style=\"text-align: right;\">     PCA_2</th><th style=\"text-align: right;\">      PCA_3</th><th style=\"text-align: right;\">  payment_type_</th><th style=\"text-align: right;\">  lightgbm_prediction</th><th style=\"text-align: right;\">  onehot_payment_type__1</th><th style=\"text-align: right;\">  onehot_payment_type__2</th><th style=\"text-align: right;\">  onehot_payment_type__3</th><th style=\"text-align: right;\">  onehot_payment_type__4</th><th style=\"text-align: right;\">  onehot_payment_type__5</th><th style=\"text-align: right;\">  onehot_pu_hour_0</th><th style=\"text-align: right;\">  onehot_pu_hour_1</th><th style=\"text-align: right;\">  onehot_pu_hour_2</th><th style=\"text-align: right;\">  onehot_pu_hour_3</th><th style=\"text-align: right;\">  onehot_pu_hour_4</th><th style=\"text-align: right;\">  onehot_pu_hour_5</th><th style=\"text-align: right;\">  onehot_pu_hour_6</th><th style=\"text-align: right;\">  onehot_pu_hour_7</th><th style=\"text-align: right;\">  onehot_pu_hour_8</th><th style=\"text-align: right;\">  onehot_pu_hour_9</th><th style=\"text-align: right;\">  onehot_pu_hour_10</th><th style=\"text-align: right;\">  onehot_pu_hour_11</th><th style=\"text-align: right;\">  onehot_pu_hour_12</th><th style=\"text-align: right;\">  onehot_pu_hour_13</th><th style=\"text-align: right;\">  onehot_pu_hour_14</th><th style=\"text-align: right;\">  onehot_pu_hour_15</th><th style=\"text-align: right;\">  onehot_pu_hour_16</th><th style=\"text-align: right;\">  onehot_pu_hour_17</th><th style=\"text-align: right;\">  onehot_pu_hour_18</th><th style=\"text-align: right;\">  onehot_pu_hour_19</th><th style=\"text-align: right;\">  onehot_pu_hour_20</th><th style=\"text-align: right;\">  onehot_pu_hour_21</th><th style=\"text-align: right;\">  onehot_pu_hour_22</th><th style=\"text-align: right;\">  onehot_pu_hour_23</th><th style=\"text-align: right;\">  onehot_pu_day_of_week_0</th><th style=\"text-align: right;\">  onehot_pu_day_of_week_1</th><th style=\"text-align: right;\">  onehot_pu_day_of_week_2</th><th style=\"text-align: right;\">  onehot_pu_day_of_week_3</th><th style=\"text-align: right;\">  onehot_pu_day_of_week_4</th><th style=\"text-align: right;\">  onehot_pu_day_of_week_5</th><th style=\"text-align: right;\">  onehot_pu_day_of_week_6</th><th style=\"text-align: right;\">  onehot_pu_month_0</th><th style=\"text-align: right;\">  onehot_pu_month_1</th><th style=\"text-align: right;\">  onehot_pu_month_2</th><th style=\"text-align: right;\">  onehot_pu_month_3</th><th style=\"text-align: right;\">  onehot_pu_month_4</th><th style=\"text-align: right;\">  onehot_pu_month_5</th><th style=\"text-align: right;\">  onehot_pu_month_6</th><th style=\"text-align: right;\">  onehot_pu_month_7</th><th style=\"text-align: right;\">  onehot_pu_month_8</th><th style=\"text-align: right;\">  onehot_pu_month_9</th><th style=\"text-align: right;\">  onehot_pu_month_10</th><th style=\"text-align: right;\">  onehot_pu_month_11</th><th style=\"text-align: right;\">  standard_scaled_arc_distance_miles</th><th style=\"text-align: right;\">  standard_scaled_direction_angle</th><th style=\"text-align: right;\">  standard_scaled_trip_distance</th><th style=\"text-align: right;\">  linear_prediction</th><th style=\"text-align: right;\">  final_prediction</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td><i style='opacity: 0.6'>0</i></td><td>VTS        </td><td>2009-01-04 02:52:00.000000000</td><td>2009-01-04 03:02:00.000000000</td><td style=\"text-align: right;\">                1</td><td>CASH          </td><td style=\"text-align: right;\">           2.63</td><td style=\"text-align: right;\">          -73.992 </td><td style=\"text-align: right;\">          40.7216</td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.9938</td><td style=\"text-align: right;\">           40.6959</td><td style=\"text-align: right;\">          8.9</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        0   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">          9.4 </td><td style=\"text-align: right;\">        15.78   </td><td style=\"text-align: right;\">            10     </td><td style=\"text-align: right;\">           3.38403</td><td style=\"text-align: right;\">        2</td><td style=\"text-align: right;\">               6</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">                  0.504949</td><td style=\"text-align: right;\">                 0.504949</td><td style=\"text-align: right;\">            0.504949</td><td style=\"text-align: right;\">        -175.882 </td><td style=\"text-align: right;\"> 0.0307305</td><td style=\"text-align: right;\"> 0.0126052 </td><td style=\"text-align: right;\">-0.0546334</td><td style=\"text-align: right;\">-0.0217226 </td><td style=\"text-align: right;\">              2</td><td style=\"text-align: right;\">             10.3132 </td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       1</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 1</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        1</td><td style=\"text-align: right;\">                  1</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                   0</td><td style=\"text-align: right;\">                   0</td><td style=\"text-align: right;\">                           -0.614417</td><td style=\"text-align: right;\">                        -1.56023 </td><td style=\"text-align: right;\">                       0.189254</td><td style=\"text-align: right;\">            9.09024</td><td style=\"text-align: right;\">           9.70172</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1</i></td><td>VTS        </td><td>2009-01-04 03:31:00.000000000</td><td>2009-01-04 03:38:00.000000000</td><td style=\"text-align: right;\">                3</td><td>Credit        </td><td style=\"text-align: right;\">           4.55</td><td style=\"text-align: right;\">          -73.9821</td><td style=\"text-align: right;\">          40.7363</td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.9558</td><td style=\"text-align: right;\">           40.768 </td><td style=\"text-align: right;\">         12.1</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        2   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">         14.6 </td><td style=\"text-align: right;\">        39      </td><td style=\"text-align: right;\">             7     </td><td style=\"text-align: right;\">           2.65934</td><td style=\"text-align: right;\">        3</td><td style=\"text-align: right;\">               6</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">                  1.91233 </td><td style=\"text-align: right;\">                 1.91233 </td><td style=\"text-align: right;\">            1.91233 </td><td style=\"text-align: right;\">          39.5963</td><td style=\"text-align: right;\"> 0.0133606</td><td style=\"text-align: right;\"> 0.00910222</td><td style=\"text-align: right;\"> 0.0255291</td><td style=\"text-align: right;\">-0.0070996 </td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">             11.5502 </td><td style=\"text-align: right;\">                       1</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 1</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        1</td><td style=\"text-align: right;\">                  1</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                   0</td><td style=\"text-align: right;\">                   0</td><td style=\"text-align: right;\">                            0.490347</td><td style=\"text-align: right;\">                         0.537361</td><td style=\"text-align: right;\">                       1.22485 </td><td style=\"text-align: right;\">           13.0823 </td><td style=\"text-align: right;\">          12.3163 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>2</i></td><td>DDS        </td><td>2009-01-01 20:52:58.000000000</td><td>2009-01-01 21:14:00.000000000</td><td style=\"text-align: right;\">                1</td><td>CREDIT        </td><td style=\"text-align: right;\">           5   </td><td style=\"text-align: right;\">          -73.9743</td><td style=\"text-align: right;\">          40.791 </td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.9966</td><td style=\"text-align: right;\">           40.7318</td><td style=\"text-align: right;\">         14.9</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        3.05</td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">         18.45</td><td style=\"text-align: right;\">        14.2631 </td><td style=\"text-align: right;\">            21.0333</td><td style=\"text-align: right;\">           2.98   </td><td style=\"text-align: right;\">       20</td><td style=\"text-align: right;\">               3</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              0</td><td style=\"text-align: right;\">                  1.90838 </td><td style=\"text-align: right;\">                 1.90838 </td><td style=\"text-align: right;\">            1.90838 </td><td style=\"text-align: right;\">        -159.335 </td><td style=\"text-align: right;\">-0.0307168</td><td style=\"text-align: right;\">-0.0241663 </td><td style=\"text-align: right;\">-0.0280609</td><td style=\"text-align: right;\"> 0.00261305</td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">             19.7338 </td><td style=\"text-align: right;\">                       1</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  1</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        1</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                  1</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                   0</td><td style=\"text-align: right;\">                   0</td><td style=\"text-align: right;\">                            0.487246</td><td style=\"text-align: right;\">                        -1.39915 </td><td style=\"text-align: right;\">                       1.46757 </td><td style=\"text-align: right;\">           18.5566 </td><td style=\"text-align: right;\">          19.1452 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>3</i></td><td>DDS        </td><td>2009-01-24 16:18:23.000000000</td><td>2009-01-24 16:24:56.000000000</td><td style=\"text-align: right;\">                1</td><td>CASH          </td><td style=\"text-align: right;\">           0.4 </td><td style=\"text-align: right;\">          -74.0016</td><td style=\"text-align: right;\">          40.7194</td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -74.0084</td><td style=\"text-align: right;\">           40.7203</td><td style=\"text-align: right;\">          3.7</td><td style=\"text-align: right;\">        0  </td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        0   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">          3.7 </td><td style=\"text-align: right;\">         3.66412</td><td style=\"text-align: right;\">             6.55  </td><td style=\"text-align: right;\">           9.25   </td><td style=\"text-align: right;\">       16</td><td style=\"text-align: right;\">               5</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              1</td><td style=\"text-align: right;\">                  0.470047</td><td style=\"text-align: right;\">                 0.470047</td><td style=\"text-align: right;\">            0.470047</td><td style=\"text-align: right;\">         -81.9194</td><td style=\"text-align: right;\"> 0.0390947</td><td style=\"text-align: right;\"> 0.00737469</td><td style=\"text-align: right;\">-0.0444038</td><td style=\"text-align: right;\"> 0.00481617</td><td style=\"text-align: right;\">              2</td><td style=\"text-align: right;\">              4.30183</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       1</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  1</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        1</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                  1</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                   0</td><td style=\"text-align: right;\">                   0</td><td style=\"text-align: right;\">                           -0.641814</td><td style=\"text-align: right;\">                        -0.645546</td><td style=\"text-align: right;\">                      -1.01355 </td><td style=\"text-align: right;\">            6.25763</td><td style=\"text-align: right;\">           5.27973</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>4</i></td><td>DDS        </td><td>2009-01-16 22:35:59.000000000</td><td>2009-01-16 22:43:35.000000000</td><td style=\"text-align: right;\">                2</td><td>CASH          </td><td style=\"text-align: right;\">           1.2 </td><td style=\"text-align: right;\">          -73.9898</td><td style=\"text-align: right;\">          40.735 </td><td style=\"text-align: right;\">        nan</td><td style=\"text-align: right;\">                 nan</td><td style=\"text-align: right;\">           -73.985 </td><td style=\"text-align: right;\">           40.7245</td><td style=\"text-align: right;\">          6.1</td><td style=\"text-align: right;\">        0.5</td><td style=\"text-align: right;\">      nan</td><td style=\"text-align: right;\">        0   </td><td style=\"text-align: right;\">             0</td><td style=\"text-align: right;\">          6.6 </td><td style=\"text-align: right;\">         9.47368</td><td style=\"text-align: right;\">             7.6   </td><td style=\"text-align: right;\">           5.08333</td><td style=\"text-align: right;\">       22</td><td style=\"text-align: right;\">               4</td><td style=\"text-align: right;\">         0</td><td style=\"text-align: right;\">              0</td><td style=\"text-align: right;\">                  0.386479</td><td style=\"text-align: right;\">                 0.386479</td><td style=\"text-align: right;\">            0.386479</td><td style=\"text-align: right;\">         155.526 </td><td style=\"text-align: right;\"> 0.0197343</td><td style=\"text-align: right;\"> 0.00458489</td><td style=\"text-align: right;\">-0.0267306</td><td style=\"text-align: right;\">-0.0110029 </td><td style=\"text-align: right;\">              2</td><td style=\"text-align: right;\">              8.9789 </td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       1</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                       0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                 0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  1</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        1</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                        0</td><td style=\"text-align: right;\">                  1</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                  0</td><td style=\"text-align: right;\">                   0</td><td style=\"text-align: right;\">                   0</td><td style=\"text-align: right;\">                           -0.707412</td><td style=\"text-align: right;\">                         1.66589 </td><td style=\"text-align: right;\">                      -0.582053</td><td style=\"text-align: right;\">            7.74905</td><td style=\"text-align: right;\">           8.36398</td></tr>\n",
       "</tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "  #  vendor_id    pickup_datetime                dropoff_datetime                 passenger_count  payment_type      trip_distance    pickup_longitude    pickup_latitude    rate_code    store_and_fwd_flag    dropoff_longitude    dropoff_latitude    fare_amount    surcharge    mta_tax    tip_amount    tolls_amount    total_amount    trip_speed_mph    trip_duration_min    fare_by_distance    pu_hour    pu_day_of_week    pu_month    pu_is_weekend    arc_distance_miles_numpy    arc_distance_miles_cuda    arc_distance_miles    direction_angle       PCA_0        PCA_1       PCA_2        PCA_3    payment_type_    lightgbm_prediction    onehot_payment_type__1    onehot_payment_type__2    onehot_payment_type__3    onehot_payment_type__4    onehot_payment_type__5    onehot_pu_hour_0    onehot_pu_hour_1    onehot_pu_hour_2    onehot_pu_hour_3    onehot_pu_hour_4    onehot_pu_hour_5    onehot_pu_hour_6    onehot_pu_hour_7    onehot_pu_hour_8    onehot_pu_hour_9    onehot_pu_hour_10    onehot_pu_hour_11    onehot_pu_hour_12    onehot_pu_hour_13    onehot_pu_hour_14    onehot_pu_hour_15    onehot_pu_hour_16    onehot_pu_hour_17    onehot_pu_hour_18    onehot_pu_hour_19    onehot_pu_hour_20    onehot_pu_hour_21    onehot_pu_hour_22    onehot_pu_hour_23    onehot_pu_day_of_week_0    onehot_pu_day_of_week_1    onehot_pu_day_of_week_2    onehot_pu_day_of_week_3    onehot_pu_day_of_week_4    onehot_pu_day_of_week_5    onehot_pu_day_of_week_6    onehot_pu_month_0    onehot_pu_month_1    onehot_pu_month_2    onehot_pu_month_3    onehot_pu_month_4    onehot_pu_month_5    onehot_pu_month_6    onehot_pu_month_7    onehot_pu_month_8    onehot_pu_month_9    onehot_pu_month_10    onehot_pu_month_11    standard_scaled_arc_distance_miles    standard_scaled_direction_angle    standard_scaled_trip_distance    linear_prediction    final_prediction\n",
       "  0  VTS          2009-01-04 02:52:00.000000000  2009-01-04 03:02:00.000000000                  1  CASH                       2.63            -73.992             40.7216          nan                   nan             -73.9938             40.6959            8.9          0.5        nan          0                  0            9.4           15.78                 10                  3.38403          2                 6           0                1                    0.504949                   0.504949              0.504949          -175.882    0.0307305   0.0126052   -0.0546334  -0.0217226                 2               10.3132                          0                         1                         0                         0                         0                   0                   0                   1                   0                   0                   0                   0                   0                   0                   0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                          0                          0                          0                          0                          0                          0                          1                    1                    0                    0                    0                    0                    0                    0                    0                    0                    0                     0                     0                             -0.614417                          -1.56023                          0.189254              9.09024             9.70172\n",
       "  1  VTS          2009-01-04 03:31:00.000000000  2009-01-04 03:38:00.000000000                  3  Credit                     4.55            -73.9821            40.7363          nan                   nan             -73.9558             40.768            12.1          0.5        nan          2                  0           14.6           39                     7                  2.65934          3                 6           0                1                    1.91233                    1.91233               1.91233             39.5963   0.0133606   0.00910222   0.0255291  -0.0070996                 1               11.5502                          1                         0                         0                         0                         0                   0                   0                   0                   1                   0                   0                   0                   0                   0                   0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                          0                          0                          0                          0                          0                          0                          1                    1                    0                    0                    0                    0                    0                    0                    0                    0                    0                     0                     0                              0.490347                           0.537361                         1.22485              13.0823             12.3163\n",
       "  2  DDS          2009-01-01 20:52:58.000000000  2009-01-01 21:14:00.000000000                  1  CREDIT                     5               -73.9743            40.791           nan                   nan             -73.9966             40.7318           14.9          0.5        nan          3.05               0           18.45          14.2631               21.0333             2.98            20                 3           0                0                    1.90838                    1.90838               1.90838           -159.335   -0.0307168  -0.0241663   -0.0280609   0.00261305                1               19.7338                          1                         0                         0                         0                         0                   0                   0                   0                   0                   0                   0                   0                   0                   0                   0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    1                    0                    0                    0                          0                          0                          0                          1                          0                          0                          0                    1                    0                    0                    0                    0                    0                    0                    0                    0                    0                     0                     0                              0.487246                          -1.39915                          1.46757              18.5566             19.1452\n",
       "  3  DDS          2009-01-24 16:18:23.000000000  2009-01-24 16:24:56.000000000                  1  CASH                       0.4             -74.0016            40.7194          nan                   nan             -74.0084             40.7203            3.7          0          nan          0                  0            3.7            3.66412               6.55               9.25            16                 5           0                1                    0.470047                   0.470047              0.470047           -81.9194   0.0390947   0.00737469  -0.0444038   0.00481617                2                4.30183                         0                         1                         0                         0                         0                   0                   0                   0                   0                   0                   0                   0                   0                   0                   0                    0                    0                    0                    0                    0                    0                    1                    0                    0                    0                    0                    0                    0                    0                          0                          0                          0                          0                          0                          1                          0                    1                    0                    0                    0                    0                    0                    0                    0                    0                    0                     0                     0                             -0.641814                          -0.645546                        -1.01355               6.25763             5.27973\n",
       "  4  DDS          2009-01-16 22:35:59.000000000  2009-01-16 22:43:35.000000000                  2  CASH                       1.2             -73.9898            40.735           nan                   nan             -73.985              40.7245            6.1          0.5        nan          0                  0            6.6            9.47368               7.6                5.08333         22                 4           0                0                    0.386479                   0.386479              0.386479           155.526    0.0197343   0.00458489  -0.0267306  -0.0110029                 2                8.9789                          0                         1                         0                         0                         0                   0                   0                   0                   0                   0                   0                   0                   0                   0                   0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    0                    1                    0                          0                          0                          0                          0                          1                          0                          0                    1                    0                    0                    0                    0                    0                    0                    0                    0                    0                     0                     0                             -0.707412                           1.66589                         -0.582053              7.74905             8.36398"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### Display the DataFrame\n",
    "df_train.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-12T16:03:48.876216Z",
     "start_time": "2019-07-12T16:03:42.795715Z"
    }
   },
   "outputs": [],
   "source": [
    "mae_train_score = mean_absolute_error(df_train[:1_000_000].trip_duration_min.values, \n",
    "                                      df_train[:1_000_000].final_prediction.values)\n",
    "mse_train_score = mean_squared_error(df_train[:1_000_000].trip_duration_min.values, \n",
    "                                     df_train[:1_000_000].final_prediction.values)\n",
    "\n",
    "print('The mean absolute error is %2.3f' % mae_train_score)\n",
    "print('The mean squared score is %2.3f' % mse_train_score)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### So what about a pipeline?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The `vaex` `state` – all the pipeline you need!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:24:12.194676Z",
     "start_time": "2019-07-13T14:24:12.133046Z"
    }
   },
   "outputs": [],
   "source": [
    "# Save the state to disk\n",
    "state = df_train.state_write('./taxi_ml_state.json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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